Online Grocery Shopping:

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Master in Business Administration - Major in Marketing

Online Grocery Shopping: An exploratory study of consumer decision making processes

JOANA MARGARIDA CALDAS DA SILVA PENIM

ADVISOR: ANA ISABEL DE ALMEIDA COSTA

Dissertation submitted in partial fulfillment of the requirements for the degree of MSc in Business Administration at Católica Lisbon School of Business & Economics March 2013

ACKNOLEDGEMENTS

First and foremost, I would like to thank all of those who collaborated in the data collection phase, either by helping in reaching possible participants and/or actively serving as study subjects. Without them, this dissertation would not have been possible. Secondly, I would like to thank my academic supervisor Doutora Ana Isabel Costa, as her expertise helped contribute to the final quality of this project. Last, but most definitely, not least, I would like to show my gratitude to all my friends and family, for all the love and support they have given me during this period. Particularly, I would like to thank my parents for all the effort and support they have given towards my academic and professional success, and to whom I would like to dedicate this dissertation.

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ABSTRACT

Online Grocery Shopping: An exploratory study of consumer decision making processes

Joana Penim

Online shopping has been known as a rapidly growing business, and although online grocery shopping has not followed these same growth patterns in the past, it is now being recognized for its potential. As such, the focus of previous online shopping research has seldom encompassed this specific retail market, with the existing studies focusing essentially on consumers’ motivations and attitudes, rather than how consumers actually shop for groceries online. Therefore, this dissertation has the objective of uncovering some of the details of consumer decision making processes for this specific online retail market, details which can help further both academic research and managerial knowledge. The general consumer decision making process is characterized by a pre-decisional, a decisional and a post-decisional phase. All of which were addressed in an exploratory fashion, through a mixed methods strategy which combined both quantitative and qualitative methods of data collection. One of the main results obtained through this study is the complementarity of retail channels - as it was found that online grocery shopping serves essentially for major shopping trips, being complemented with smaller trips to traditional stores. Moreover, some resistance to online grocery shopping, specifically the shopping of fresh produce, was also still found among the Portuguese population. Additionally, based on two of the main consumer shopping orientations which shape online grocery shopping, price-sensitivity and convenience, this study uncovered consumer groups which presented distinguishable shopping strategies. These strategies are in general very focused and rational, and vary essentially based on the shopper’s more prominent shopping orientation. Moreover, all consumer types were found to have general negative responses to online stimuli present during shopping. Thus, this dissertation contributed to the knowledge of consumer decision making processes for online grocery shopping, making wave for new and further researches in this field and contributing to managerial knowledge.

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SUMÁRIO

Compras de Supermercado Online: Um estudo exploratório sobre processos de decisão do consumidor

Joana Penim

A compra online é conhecida como um negócio de rápido crescimento, e embora as compras de supermercado online não tenham no passado seguido este mesmo padrão de crescimento, estão agora a ver o seu potencial reconhecido. Desta forma, a investigação relativa a compras online não tem tido por foco esta categoria específica de produtos, já que os poucos estudos existentes se centraram essencialmente nas motivações e atitudes dos consumidores e não na forma como estes realmente efectuam as suas compras. Desta forma, esta tese tem por objectivo estudar os detalhes dos processos de decisão dos consumidores relativamente à compra de supermercado online. Detalhes estes que podem ser de relevante importância no avanço, tanto da pesquisa académica, como do conhecimento empresarial. Em geral, o processo de decisão do consumidor é caracterizado por três fases, uma fase antes da compra, a fase durante a compra e uma última fase após a compra. Tendo as três fases referidas sido abordadas de uma forma exploratória, através de uma estratégia de métodos mistos que combina métodos de recolha de dados quantitativos e qualitativos. Um dos principais resultados obtidos com este estudo, depreende-se pela complementaridade de canais de distribuição. Tendo sido descoberto que a compra de supermercado online serve essencialmente para uma compra maior (por exemplo, a compra do mês), sendo complementada com compras de menor dimensão em lojas tradicionais (por exemplo, a compra da semana ou diária). Adicionalmente, foi ainda encontrada alguma resistência a este tipo de compra online entre a população Portuguesa, especificamente no que toca a compra de produtos frescos. Para além destes resultados, e com base em duas das orientações de compra que guiam a compra de supermercado online mais importantes (sensibilidade ao preço e conveniência), este projecto permitiu ainda encontrar grupos de consumidores com estratégias de compra distintas. Estas estratégias são em geral focadas e racionais, mas variam com base na orientação de compra do consumidor mais proeminente. Todos os tipos de consumidores encontrados mostraram ainda respostas, em geral, negativas quanto aos estímulos online presentes durante a compra. Assim, é possível constatar que esta tese de mestrado contribuiu para o conhecimento dos processos de decisão do consumidor para compras de supermercado online, abrindo vaga para novas e futuras pesquisas académicas na área, assim como contribuindo para o conhecimento desta actividade comercial.

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Table of Contents CHAPTER 1: INTRODUCTION ..................................................................................... 6 1.1. Background and problem statement ..................................................................... 6 1.2. Aims and scope ..................................................................................................... 7 1.3. Methodology ......................................................................................................... 8 1.4. Relevance and implications .................................................................................. 9 1.5. Dissertation outline ............................................................................................. 10 CHAPTER 2: LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK........ 11 2.1. The purchase decision making process in traditional retail environments .......... 11 2.2. The purchase decision making process in online retail environments ................. 12 2.3. Grocery shopping in traditional stores ................................................................. 13 2.3.1. Pre-decisional stages ......................................................................................... 14 2.3.2. In-store buying decisions .................................................................................. 16 2.4. Grocery shopping in online stores ....................................................................... 17 2.4.1. Adoption and buying motivations..................................................................... 18 2.4.2. Buying, browsing and search patterns .............................................................. 20 2.5. Main conclusions & conceptual framework ........................................................ 21 CHAPTER 3: METHODOLOGY .................................................................................. 24 3.1. Research purpose and approach ........................................................................... 24 3.2. Research strategy and design ............................................................................... 24 3.3. Population and sampling ...................................................................................... 26 3.4. Data collection ..................................................................................................... 27 Web-based questionnaire ........................................................................................ 27 Semi-structured interviews and accompanied shopping visits ................................ 28 3.5. Data analysis ........................................................................................................ 30 Web-based questionnaire ........................................................................................ 30 Semi-structured interviews and accompanied shopping visits ................................ 31 CHAPTER 4: RESULTS’ ANALYSIS & DISCUSSION ............................................. 32 4.1. Results of the web-based questionnaire ............................................................... 32 4.2. Results from the semi-structured interviews and accompanied shopping visits.. 36 4.2.1. Pre-decisional phase.......................................................................................... 37 Planning................................................................................................................... 37 4

Inter- & Intra-Purchase Cycles ................................................................................ 38 4.2.2. Decisional phase ............................................................................................... 39 Buying and browsing strategies .............................................................................. 39 Response to Stimuli................................................................................................. 42 4.2.3. Post-decisional phase ........................................................................................ 43 4.3. Resulting propositions ......................................................................................... 44 CHAPTER 5: CONCLUSIONS ..................................................................................... 46 5.1. Conclusions & Suggestions ................................................................................. 46 Managerial suggestions ........................................................................................... 48 5.2. Limitations ........................................................................................................... 49 5.3. Future Research ................................................................................................... 50 REFERENCES ............................................................................................................... 51 ANNEX 1 – Web-based questionnaire for online grocery shopping ............................. 56 ANNEX 2 – Script for the semi-structured interviews and observation of shopping trip ........................................................................................................................................ 57 ANNEX 3 – Continente Online Store Layout ................................................................ 60 ANNEX 4 – Tesco’s Store Layout with ‘multisearch’ tool............................................ 60

LIST OF FIGURES Figure 2.1. – Conceptual Framework ……………………………………………...…. 21

LIST OF TABLES Table 4.1 – Demographic Characteristics (n=55) ……….………………....……........ 32 Table 4.2 – Planning Patterns (n=49) …………………………………………….…... 35 Table 4.3 – Respondents’ profiles (n=9) ……………….……………………….….... 36

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CHAPTER 1: INTRODUCTION

1.1. Background and problem statement As pointed out by previous studies, (e.g. Lim, Widdows & Hooker, 2009; Ramus & Nielsen, 2005), the online retail market has grown tremendously over the last decades, with sales and consumer adoption increasing every year. However, this growth has been highly heterogeneous across retail segments. The online grocery business, in particular, has witnessed a difficult start in Europe and the U.S., with the online operations of established retailers and click-only grocery stores struggling to survive (e.g. Peapod, Webvan, Homegrocer, Shoplink) (e.g., Delaney-Klinger, Boyer & Frohlich, 2003; Lim, Widdows & Hooker, 2009; Ramus & Nielsen, 2005). Consequently, the scope of previous academic research related to online shopping and consumer behaviour has seldom addressed the grocery retail market, with the few existing studies focusing only on consumers’ adoption and general attitudes and motivations towards online grocery shopping (e.g. Ramachandran, Karthick & Kumar, 2011; Morganosky & Cude, 2000; Hansen, 2005; Verhoef & Langerak, 2001). As a result, not much is known about how exactly consumers shop online for groceries. In this contemporary society, bounded by the search of constant technological advances and innovations, consumers are becoming less and less loyal to any specific brand or retail format and increasingly focus on the satisfaction of immediate goals and needs (Deloitte & Harrison Group, 2010). Consequently, online shopping has become a highly profitable retail format, achieving high sales values across much of the developed world (e.g. Lim, Widdows & Hooker, 2009; Hand, Riley, Harris, Singh & Rettie, 2009). Although yet far from reaching its full potential in several markets, the current percentage of online grocery sales is certainly something to follow closely (e.g. Lim, Widdows & Hooker, 2009). As traditional and click-only grocery retailers begin to learn from past errors and learn to take better advantage of the technological innovations developed for the digital world, more companies are venturing into this segment with improved business models and service levels (Delaney-Klinger, Boyer & Frohlich, 2003). Concurrently, Western consumers are experiencing increasing time and budget constraints, both of which are impacting considerably their shopping behaviour (Morganosky & Cude 2000; POPAI, 2011; Deloitte & Harrison Group, 2010). Namely, they are becoming more value-conscious due to the current economic crisis, which 6

together with the time scarcity felt, leads to an increasing demand for lower search costs, higher shopping convenience, better price deals and more rewarding purchase experiences (e.g., Morganosky & Cude 2000; POPAI, 2011; Deloitte & Harrison Group, 2010). Such trends are likely to motivate a renewed interest in online grocery shopping in the coming years. Although several studies have looked at online grocery shopping at various levels, such as adoption (e.g., Hansen, 2005), profiling of consumer segments (e.g., Rohm and Swaminathan’s, 2004) or relationship with situational variables (e.g., Robinson, Riley, Reetie & Rolls-Willson, 2007), very few have investigated the actual purchase decision making processes of online grocery shoppers. Since grocery shopping involves purchase decisions that are markedly different from those in other product categories (Verhoef & Langerak, 2001), such as apparel or technology for instance, it is crucial for retailers to learn how their customers shop online for groceries if they want to tap into this market’s potential and thrive in the highly competitive online environment (Ramachandran, Karthick & Kumar, 2011). It becomes, therefore, necessary for retailers and managers to better understand not only what motivates their consumers to shop for groceries online in the first place, but also how online consumers go about making buying decisions in a digital environment (Hand, Riley, Harris, Singh & Rettie, 2009; Ramachandran, Karthick & Kumar, 2011). This dissertation intends to contribute to the growing body of knowledge of the consumer decision making processes in online grocery shopping environments. Namely, it will seek to explore, in as much detail as possible, how consumers purchase supermarket products in online retail stores and uncover the main features of the buying decision processes involved in this type of consumer behaviour.

1.2. Aims and scope The general aim of this dissertation is to portray a complete and detailed picture of the overall purchase decision making process of consumers shopping online for groceries, including pre- and post-decisional stages. Although providing a broad description of the overall decisional process, the intent is to focus on the actual purchasing stage, shedding some light onto two details of this process – the in-store buying and browsing strategies used by online grocery shoppers and their reaction to in-store stimuli. Specifically, this dissertation attempts to answer the following research questions: 7



What are the consumers’ buying, search and browsing strategies while looking for offers in online grocery stores?



How do consumers respond to in-store stimuli in an online grocery store environment?

For practical reasons, the scope of this dissertation’s data collection is limited to the buying behaviour of Portuguese grocery shoppers, particularly of those living in the broad Lisbon area. Portuguese consumers have a marked preference for buying groceries in large, traditional store formats, such as hypermarkets and supermarkets, a segment in which the company Sonae MC is the current market leader (GAIN Report, 2003; APED Report, 2009). To date, there are only two hypermarkets and one supermarket brand selling groceries online in Portugal, with Sonae MC also leading this segment with its brand Continente Online (GAIN Report, 2003; APED Report, 2009; Acepi, 2012). Consequently, the scope of this dissertation is limited to shopping trips conducted in the Continente Online’s website, which is also the only Portuguese online grocery store with a website up to par with current e-commerce technology.

1.3. Methodology In order to answer the research questions proposed, and given that there are no specific articles on in-store decision making processes for online grocery shopping, as indicated previously, two studies were conducted and approached in an exploratory fashion. A mixed methods strategy was chosen, more specifically a convergent parallel research design. Such a design is characterized by the concurrent, but independent collection and analysis of quantitative and qualitative data, with the aim of combining findings to obtain meaningful answers to the underlying research questions (Bryman, 2012; Creswell & Plano Clark, 2011; Tashakkori & Teddlie, 2003). The first study elaborated consisted of an online questionnaire directed towards Portuguese online grocery shoppers of Continente Online (n=55), focusing on the collection of quantitative data, essentially on the pre-decisional phase of the consumer decision making process. The second study, on the other hand, consisted on the collection of qualitative data on the consumer’s behaviour inside the online store, through in-depth interviews and behavioural observation. The subjects (n=9) for the second study were recruited through the online questionnaire performed before hand, targeting Portuguese consumers 8

shopping at Continente Online and that corresponded to the desired characteristics (i.e. constituting an overall balanced sample). It is important to acknowledge that the qualitative aspect of this methodology encompasses a higher weight of the overall analysis, compared with the contrasting quantitative feature, given that the qualitative facet focuses essentially on the decisional phase of the online grocery shopper decision making process – the focal point of the research questions defined. The methods described were based on the Shopping with Consumers observational method used in instore traditional retailing (Lowrey, Otnes & McGrath, 2005). This method, although usually used in in-store retailing, was adapted for this dissertation due to the proximity with the informant, which provides a better understanding of consumers’ behaviour instore, being more advantageous for the study proposed. Moreover, the combination of both quantitative and qualitative methods, allows for a more complete and in-depth approach of the research questions defined. As the response to in-store stimuli, occurring exactly at the point of sale, is better acknowledged through consumer’s observations, as well as the search and browsing strategies used, although being the last also determined by pre-decisional factors. Thus, the combination of both methods was deemed the most appropriate.

1.4. Relevance and implications The findings and conclusions presented by this dissertation have both academic and practical relevance. On one hand, they support the establishment of future research studies related to online grocery shopping, uncovering new insights about consumer online behaviour within this retail category. Namely, the different strategies consumers use while shopping online for groceries and their respective response to the presented stimuli. On the other hand, these new insights and information about online grocery shoppers are also important for the success of retailers’ strategies and respective online platforms. By better understanding the buying process of online grocery shopping from the plans consumers elaborate before shopping, to the actual buying process and finally to the post-shopping evaluation – as well as some of the implications on sales of this retail channel versus a more traditional one, this study is expected to contribute to the practical knowledge of retailers, retail managers and marketers, allowing them to better adapt their online stores to the expectations and behaviour of consumers. Moreover, allowing retailers and managers to better understand how to engage 9

consumers in the different retail channels available, increase possible sales and position over competitors, and how to offer consumers the best suitable service possible given their specific consumer characteristics and preferences.

1.5. Dissertation outline Chapter 2 presents the results of the literature review performed, which focused on current knowledge about traditional and online grocery shopping behaviour. This chapter also provides details of the conceptual framework that guided the development of the dissertation. Chapter 3 details the research methodology employed to seek answers to the proposed research questions, namely the design and performance of empirical studies with online grocery shoppers, while Chapter 4 describes and analyses the results obtained from these studies. Chapter 5 summarizes the relevant conclusions and implications that can be derived from the findings of this dissertation, addresses its main limitations and proposes avenues for further research in the area of online grocery shopping.

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CHAPTER 2: LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK This chapter presents a review of the articles and business reports related to consumers’ grocery shopping decision making process, in both offline and online retail channels. The intent was to acquire a general overview of grocery shopping, in what pertains to this dissertation and subsequent research questions, and as such the focus relies mostly on the decisional phase and influencing pre-decisional phase of the grocery shopper decision making process. Based on the outcome of the literature review performed, a conceptual framework that guided the design and performance of the empirical studies, aiming at providing answers to the proposed research questions, is also presented.

2.1. The purchase decision making process in traditional retail environments A consumer purchase is typically a response to a problem or need, and once a consumer realizes this, he or she undergoes a series of steps until his or her need is satisfied (Solomon, Bamossy, Askegaard, & Hogg, 2006). This is a reflection of the consumer decision making process, which main stages are generally defined in the Consumer Behaviour and Marketing literature as: (1) Problem identification; (2) Information search; (3) Evaluation of alternatives; (4) Purchasing decision; (5) Post-purchase behaviour (e.g. Kotler & Keller, 2008; Solomon, Bamossy, Askegaard, & Hogg, 2006). However, not all decision making processes are exactly consistent with this model, as several external factors (such as consumer characteristics, motivations, socio-economic environment, etc.) may influence how consumers progress from one stage to the next (Solomon, Bamossy, Askegaard, & Hogg, 2006). In the context of the models of consumer decision making described by Solomom, Banossy, Askegaard, & Hogg (2006), grocery shopping can be best categorized as a habitual decision making process. As the decisions associated to most supermarket purchases typically demand only a low level of involvement from most consumers, being strongly related to the experience of past shopping trips and automated buying routines (Solomon, Bamossy, Askegaard, & Hogg, 2006). Nevertheless, supermarket product offers and grocery store environments are usually far more complex, information-rich and heterogeneous than those characterizing other types of purchases, encompassing a very large set of cues and stimuli designed to influence consumers’ decision making at the point of purchase. As 11

Inman, Ferraro & Winer (2004) established in their model for in-store decision making, customers are firstly exposed to product categories and in-store displays as they shop, with the intensity of exposure being highly influenced by several contextual factors, like shopping trip type, display type/location, number of aisles shopped and purchase involvement. Then, shoppers must be motivated to process the in-store stimuli to which they are exposed, a motivation which is in turn influenced by factors such as deal proneness, age and need for cognition. Next, the recognition of a need for the product category (if the consumer has not planned to purchase such category beforehand) must be acknowledged, something which again may be influenced by several factors, like compulsiveness, shopping party size, gender, household size, age and income. And finally, the actual decision execution must occur for each category purchase, independently of whether the purchase was planned beforehand or decided only inside the store.

2.2. The purchase decision making process in online retail environments When analysing the particular case of online shopping, factors other than those already reviewed come into play and should therefore be taken into account. Chen & Chang (2003) highlight three key quality dimensions that impact consumers’ satisfaction with online shopping activities and subsequent purchase: interactivity (e.g., the quality of broadband connection and the design of the website), transaction (e.g., shopping value, convenience, assurance, entertainment and evaluation) and fulfillment (e.g., order processing, delivery and post-sales service). Interactivity is closely linked to overall store satisfaction, as it can by itself demote or promote the consumer to continue browsing/searching/purchasing on a specific website. Meanwhile, the quality of the transaction process also plays a crucial role, as convenience, value and security are essential online consumer requirements. Finally, the level of fulfillment determines the confidence and trust consumers have in online transactions, and may also help to provide greater convenience and value to e-shoppers (Chen & Chang, 2003). Additionally, Constantinides (2004) reinforced the claim that, just as in traditional markets, the interaction of uncontrollable (consumer characteristics and environmental influences)

and

controllable

factors

(product/service

characteristics,

medium

characteristics, merchant/intermediary characteristics) is also at play in the online shopping environment. Consequently, the controllable traditional marketing tactics, 12

which are essential to attract and engage consumers, are paired with the online shopping experience controllable elements as to provide a satisfactory consumer online experience (Constantinides, 2004). As such, online shopping experiences are viewed as being the outcome of website functionality, user characteristics, online cues and stimuli, information provisioning and product and service offers (Constantinides, 2004). All these factors will hence serve as input for buying decisions, alongside the traditional consumer decision making variables associated to offline purchasing. Finally, in their review of previous research, Darley, Blankson & Luethge (2010) present an online decision making process model, which further segregates the external influential factors into individual differences or characteristics (i.e., motives, values, lifestyle, and personality), socio-cultural factors (i.e., culture, social class, reference groups, and family), situational and economic factors, and online atmospherics or environmental aspects (i.e., website quality, interface, user satisfaction and user experience). This model is based on the central role occupied by traditional decision making processes in the online shopping environment, recognizing the existence of particular moderating and interacting effects. Furthermore, the authors highlight the satisfaction of human needs rather than emphasizing the specifics of the underlying technology, and emphasize online consumer behaviour as a complex phenomenon, with several links and interactions that are still unexplored and offer ground for further research.

2.3. Grocery shopping in traditional stores As several studies indicate (e.g. Deloitte & Harrison Group, 2010; POPAI, 2011), grocery shoppers have begun to find ways to spend less and reduce risk in the mist of the current economic and financial crisis. They have learned new tactics to save money on supermarket purchases and manage their household pantry, while shopping trips have also become more careful and focused (Deloitte & Harrison Group, 2010). Consumers’ grocery shopping routine now regularly includes strategic and tactical features like clarifying wants versus needs, delaying gratification, lowering quality requirements, frequent channel, store and brand switching, an intense use of coupons, loyalty cards, shopping lists and other promotional offers, stockpiling and increasing purchase of private label products, among others (Deloitte & Harrison Group, 2010; POPAI, 2011). Furthermore, consumers are becoming increasingly less loyal to national 13

brands and also less likely to engage in impulse buying or new product trial, as the new aim for grocery shopping is household gratification while maintaining quality but minimizing expenditure (Deloitte & Harrison Group, 2010). Consumers are no longer afraid or ashamed to be seen shopping for a bargain, often viewing price as the single most important factor in choosing among retail brands and also a motive to patronize multiple stores, formats and retail brands (POPAI, 2011). Shoppers are also increasingly synergizing between the off- and on-line channels, in order to maximize the value of their purchases (POPAI, 2011; Deloitte & Harrison Group, 2010). To the same end, they are also becoming more receptive to new electronic shopping tools and savvier as to which fit better their purchase needs and plans, increasingly seeking all sorts of information resources available to gain more control over their shopping experience (POPAI, 2011). And while these new approaches and strategies are mostly based on cutting down expenditure, most consumers still do not feel like they are sacrificing much, and thus show no intention of returning to old shopping habits when the economy recovers (POPAI, 2011; Deloitte & Harrison Group, 2010). According to A.C. Nielsen’s annual report on consumer confidence (2010), Portuguese consumers are no exception to this scenario. As fellow shoppers worldwide, they are also changing their spending habits – e.g., eating out less, buying less garments and more private labels, being more concerned about energy and gas spending –, and show no intention of returning to old shopping habits.

2.3.1. Pre-decisional stages How purchases are actually decided upon during shopping trips is greatly influenced not only by the purchase environment, but also by several pre-decisional factors. Namely, buying decisions are heavily conditioned by the goals consumers pursue within a specific purchase, which can be as diverse as satisfaction of general needs, acquisition of essential items, emotional gratification or mere entertainment (Santos, 2009). This reflects different shopping motivations, which shape shoppers’ decision making processes, and which can be generally distinguished as being of an utilitarian or hedonic perspective (Babin, Darden & Griffin, 1994; Cardoso & Pinto, 2010). Utilitarian shoppers are problem-solving, task-oriented consumers, who make mainly rational decisions. While, on the other hand, the hedonic shopper is often looking for enjoyment, emotional and/or sensory stimulation and the satisfaction of desires while carrying out 14

their shopping activities (Babin, Darden & Griffin, 1994; Cardoso & Pinto, 2010). In the context of grocery shopping, this activity can be, for some consumers, a highly stressful chore and nothing more than a hassle, rather than pleasant and enjoyable (Santos, 2009). In this sense, and given the habitual or routine characteristic of this type of purchase, which mostly focuses on the acquisition of essential items (Santos, 2009; Solomon, Bamossy, Askegaard, & Hogg, 2006), grocery shopping is mostly considered an activity with an underlying utilitarian motivation (Babin, Darden & Griffin, 1994; Cardoso & Pinto, 2010; Santos, 2009). Concurrently, the establishment and achievement of such shopping goals implies a series of pre-decisional steps, such as when to conduct a particular shopping trip, which stores to visit or which products to choose from (Santos, 2009). As Santos (2009) states, the timing of shopping trips is defined not only by the availability of the consumer, but also by the periods when the shopper believes to be more appropriate to visit the selected stores. While the decision of which stores to visit and which products to purchase is deeply influenced by the shopper’s expectations of which alternatives will better satisfy his or hers existing needs (Santos, 2009). Additionally, other pre-shopping decisional factors such as the use or not of a shopping list or shopping alone or accompanied, for example, are also likely to influence consumers’ behaviour and shopping outcomes (Santos, 2009; POPAI, 2011; Thomas & Garland, 2004). The use of a written shopping list, for instance, can act as an important shopping tool for goal achievement. As, for some, shopping lists yield the benefits of ensuring that needed products are acquired and hence minor fill-in shopping trips are avoided. While, for others, shopping lists mean fewer hassles, as the shopping process and budget expenditure are kept under control (Thomas & Garland, 2004; Santos, 2009).

Furthermore, according to a study by the POPAI Institute (2011),

unaccompanied shoppers are less likely to use written shopping lists and more likely to deviate more from their spending goals. While, accompanied shoppers tend to navigate more throughout the store, but see companions as having little influence on their purchases (POPAI, 2011). Indeed, grocery shopping patterns are heavily determined by consumer demand and subsequent shopping plans, and this has an important effect on the time and budget spent at the store (Santos, 2009).

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2.3.2. In-store buying decisions According to POPAI’s report on grocery shopper engagement (2012), the rate of overall in-store decision making (i.e., generally planned, unplanned and substitute purchases) has climbed to 76% in 2012, with most of this rise coming down to the increase of instore marketing activities. An increasingly important part of the marketing mix is, thus, the use of point-of-sales materials and devices to stimulate sales, given that the decision making process of shoppers is often triggered just at the sight of the product category displays or related in-store stimuli (e.g., POPAI, 2012; Inman, Winer & Ferraro, 2009; Park, Iyer & Smith, 1989). Therefore, planned purchases can be defined as purchase decisions completely established before entering the store, while unplanned or impulse purchases can be defined as made specifically inside the store, and thus dependent on the existing marketing activities (e.g., Inman, Winer & Ferraro, 2009). Consequently, positive affective reactions to in-store stimuli increase the likelihood of unplanned purchases, or, in other cases, prompt consumers to consider or remember that there is a need for a certain product category which was not considered at the time when the shopping plans were made (Inman, Winer & Ferraro, 2009). Concurrently with the interaction of the shopper and the shopping environment, consumer’s proneness to unplanned purchases has also been shown to vary with out-of-store stimuli, such as overall shopping goals (Bell, Corsten & Knox, 2011). In this sense, research has shown that on major shopping trips there is a higher incidence of unplanned purchases rather than on fill-in trips, given that in-store stimuli are likely to have a higher impact on more broadly-defined purchase intentions (Kollat & Willett, 1967; Bell, Corsten & Knox, 2011). Also, consumers on major shopping trips are likely to spend more time inside the grocery store and therefore become more exposed to in-store stimuli (Kollat & Willett, 1967; Bell, Corsten & Knox, 2011). Moreover, Park, Iyer & Smith (1989) have found that time restrictions and high store familiarity limit the extent to which shoppers process in-store information, and as such, shoppers make more unplanned purchases under no time pressure and in unfamiliar stores. Additionally, Bell, Corsten & Knox, (2011) have found that on trips in which the household chooses the store based on its low prices there is more unplanned buying, as the consumer may feel its extra purchases to be justifiable. Moreover, the authors suggest that on trips in which the household chooses the store as part of a multi-store shopping strategy there are less unplanned purchases, as this reflects a strategy of more specifically-defined goals. Another important aspect of unplanned purchases was stated by Stilley, Inman & 16

Wakefield (2010), which argue that consumers anticipate the occurrence of unplanned purchases because they realize they have neither the time nor the resources to fully plan, and/or because they want to be able to make spontaneous decisions while in-store. Therefore, these authors defend that consumers establish a mental budget to spend on a specific grocery shopping trip and that this budget includes room for impulse purchases. Additionally, even when a budget is not explicitly defined, consumers will know by experience the average amount to spend due to the routinized nature of grocery shopping, and will take this into account (Stilley, Inman & Wakefield, 2010).

2.4. Grocery shopping in online stores Online grocery stores were amongst the first Internet start-ups to be launched in the late 1990’s. Nevertheless, it was only very late that this type of business was able to gain enough traction amongst North-American and European consumers, currently accounting for only a small portion of total online retail sales in many countries (KPMG International, 2012; Lim, Widdows & Hooker, 2009; Ramus & Nielsen, 2005). Nevertheless, after books, clothing and other product categories, grocery shopping is emerging as the next fastest growing category in online retailing (KPMG International, 2012). As such, the strong predicted growth of the online grocery channel in Western countries presents good business opportunities for brand manufacturers and retailers alike (Lim, Widdows & Hooker, 2009). A study by KPMG International (2012) has encountered that, in such developed countries, the largest segment of online grocery shoppers is mainly composed of highly educated (graduates or above) females, aged 25–55 years old, with a full or a part-time job and with children under their care. Due to the current economic conditions, however, this study found that more consumers from all income levels are beginning to buy groceries online, looking to benefit from the variety of promotional offers that tend to be exclusive to this retail format. Additionally, the KPMG International (2012) study uncovered that consumers are gradually shifting from personal computers to mobile phone and tablets as the preferred device for online shopping. Consequently, the continued development of mobile applications and its increased convenience of use and associated services should help increase even more the occurrence of online grocery shopping (KPMG International, 2012). Moreover, the referred study defends that online grocery stores offer the contemporary, time and money tight customers a way to conveniently search and acquire products, alongside 17

with the opportunity to more easily control their budget and closely monitor their cart contents (KPMG International, 2012). Thus, the aspect that seems to be, at least, one of the main drivers for online shoppers is the need for convenient shopping activities (e.g., Rohm and Swaminathan’s, 2004; Morganosky & Cude, 2000; Ramus & Nielsen, 2005; Verhoef & Langerak, 2001; Robinson, Riley, Reetie & Rolls-Willson, 2007). The study performed by Rohm & Swaminatham (2004), for instance, confirms this result arguing that convenience, paired with variety seeking, are the main underlying motivations in the online channel, while time savings and recreational shopping orientations appear to be more significant drivers in the offline store format. Although convenience remains important in both retail channels, one possible explanation the authors found for the differentiating drivers between store formats may be that, while there is time saved in shopping online, there is also a higher time gap between purchase and actual acquisition of the goods purchased, due to the delivery waiting periods.

2.4.1. Adoption and buying motivations “Digital retailing is playing an increasingly pivotal role in the way consumers shop, having changed their expectations and preferences considerably” (KPMG International, 2012). This development also applies to the online grocery store business, as a study undertaken by Hansen (2005) indicates that, on average, consumers are now well familiar with online grocery stores and do not associate a particularly higher risk of shopping online for grocery products, when compared to other product categories. Yet, there are still some strong barriers to widespread online grocery shopping adoption, namely consumer skepticism and uncertainty, the payment of delivery fees, the occurrence of delayed and/or wrong deliveries, a lack of/lower level of online promotional activities, a higher task complexity and insufficiently user-friendly websites (Robinson, Riley, Reetie & Rolls-Willson, 2007; KPMG International, 2012). These perceived drawbacks lower the trust of potential customers on online transactions, decrease conversion rates from browsers to shoppers, reduce basket sizes and limit the number of returning customers (KPMG International, 2012). Additionally, it is suspected that consumers continue to shop for groceries offline out of habit, or due to a lack of awareness and actual availability of online options (Nielsen, 2009). These are unfortunate circumstances, as more consumers increasingly appreciate the opportunity to shop day and night for groceries and avoid the unpleasant experiences 18

that can accompany shopping in traditional stores, such as crowds or traffic (Nielsen, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007; Morganosky & Cude, 2000). Furthermore, online grocery shopping allows consumers to buy in bulk and stock up without having to lug around heavy packages (Nielsen, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007). Finally, it helps time-restricted consumers to save time and money, and can become a less stressful way of shopping, one in which consumers exercise greater control over their purchases and better compare products and offers (KPMG International, 2012; Nielsen, 2009; Verhoef & Langerak, 2001). As such, more evidence is provided which denotes shopping convenience as one of the main drivers for online grocery shopping (e.g., Nielsen, 2009; Verhoef & Langerak, 2001). Accordingly, Robinson, Riley, Reetie & Rolls-Willson (2007), supporting earlier findings by Morganosky & Cude (2000), noted that convenience seems particularly relevant when some situational constraints - such as ill health, changing homes or jobs, breaking a limb, having a baby, working late, children leaving home, working from home, aging, etc. – come into play. In addition, the authors argue that the disappearance of such situational constraints is also often the primary reason for stopping or diminishing the frequency of online grocery shopping. In this sense, online grocery shopping has been found to be, by several studies, highly discretionary (Hand, Riley, Harris, Singh & Rettie, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007; Morganosky & Cude, 2000), as it may be forsaken when a specific trigger disappears or when, for some reason, consumers become unhappy with the level of service. This indicates that even the high demand for convenience that often drives the adoption of online grocery shopping may be highly contingent upon particular individual circumstances (Hand, Riley, Harris, Singh & Rettie, 2009). This leads to the frequent re-evaluation of the decision to conduct grocery shopping in online formats. Consequently, post-adoption evaluations become particularly crucial to the decision of whether or not to continue using an online grocery store (Hand, Riley, Harris, Singh & Rettie, 2009). Taken together, past findings suggest that online grocery shopping is complementary to, rather than a substitute of, traditional grocery shopping (Hand, Riley, Harris, Singh & Rettie, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007; Morganosky & Cude, 2000). As evidence has been found that most consumers shop personally, at least, for perishables and/or special products (i.e., items shopped with an uncommon purpose, as for example a dinner party) (Robinson, Riley, Reetie & RollsWillson, 2007; Morganosky & Cude, 2000). 19

2.4.2. Buying, browsing and search patterns Some studies have investigated consumers’ search and browsing patterns for several product categories, within the online environment (e.g. Moe, 2003; Wolfinbarger & Gilly, 2001). In a research by Moe (2003), for example, a distinction between goaldirected search and exploratory search is made. On one hand, exploratory search is less deliberate and focused on a particular purchase occasion. It tends to be more undirected and stimulus-driven than goal-driven, hence being often referred to as browsing or ongoing search, and in many instances derives from consumers’ poor familiarity with product categories. Goal-directed search, on the other hand, refers to situations in which online consumers browse the web with a specific or planned purchase in mind. In this case, search patterns are very focused and driven towards goal achievement. As a result, goal-directed searches are highly task-oriented, rational, efficient and deliberate (Moe, 2003; Wolfinbarger & Gilly, 2001). Furthermore, goal-oriented consumers reach control, freedom and lack of commitment in the online channel, as they encounter little pressure to purchase before they are completely ready, and are thus found to be less impulsive (Wolfinbarger & Gilly, 2001). Additionally, and as previously mentioned, online grocery shopping, as offline grocery shopping, is considered by most consumers as a chore, an activity which is performed mainly by utilitarian, rather than hedonic, shopping motivations (Robinson, Riley, Reetie & Rolls-Willson, 2007; Verhoef & Langerak, 2001), and which is highly directed towards goal achievement (POPAI, 2012). Thus, online grocery store visits should be considered as directed-buying internet visits, which are more likely to result in immediate purchases (Moe, 2003). A typical characteristic of such directed-buying visits is the consumer’s tendency to present focused search patterns, which represent the shopper’s goal-driven motivation (Moe, 2003). This, however, does not totally exclude the possibility of exploratory search behaviours at the category, product or even brand level and hence does not necessarily preclude the incidence of in-store decision-making, depending also on the extent and nature of the encountered stimuli (Moe, 2003). In regards to online stimuli, a study conducted by Parsons & Conroy (2006) suggests that grocery websites provide examples of the middle ground concerning the relationship between stimuli and the browsing experience. Given that online grocery stores are more likely to have frequent repeat visits, consumers should be more pervious to familiar stimuli and would not want to become over-stimulated, relatively to what happens in traditional stores (Parsons & Conroy, 2006). In addition, the referred study uncovered that, online grocery shoppers 20

have a preference for fast tempo, low volume music and average pitch, and that the matching of these requirements would likely increase the time spent browsing the store. Finally, regarding visual stimuli, there is an indication that colours and brightness were likely to improve the shoppers’ perception of the products’ quality, possibly leading to increased browsing. However, too many animations, videos or fonts are likely to have an adverse effect on browsing and store perceptions (Parsons & Conroy, 2006).

2.5. Main conclusions & conceptual framework The literature reviewed allowed for the understanding of the main characteristics of both offline and online grocery shopping, setting a framework of the most important factors influencing the consumer’s online decision making process. While establishing a baseline for online grocery shopping, as to support this dissertation in its quality of exploratory study and in what relates to the problem statement and research questions defined. Figure 2.2, shows the conceptual framework designed to guide the elaboration of the field study.

Pre-decisional stage

Decisional stage

Post-decisional stage

Consumer Decision Making Process

Consumer inter-related variables Consumer shopping plans and patterns • Shopping frequency • Shopping schedule • Shopping means • Shopping budgets • Shopping lists • Accompanied shopping • Level of planning

• Multi-store strategy & store preference • Product categories purchase preferences • Promotional activities’ search

Consumer socio-demographic characteristics • Income • Gender • Age • Education • Household

In-store controllable variables Online environment & stimuli • Promotional stimuli • Store Design & Interactivity

Consumer shopping orientations • Convenience Orientation • Price-Sensitivity Orientation • Impulsiveness Consumer purchase strategies • Response to online stimuli • Buying and browsing strategies

Figure 2.1. – Conceptual Framework.

According to several studies (e.g. POPAI, 2011), consumers are changing their shopping habits and show no signs of returning to old patterns. Shoppers are becoming 21

savvier and more concerned with money and time savings, which helps to explain the increase of online grocery shopping and its tendency for growth. Although this growth is shown across consumers of most income levels, the largest consumer segment is composed of highly educated employed females, aged 25 to 55 years old, with children (KPMG International, 2012). Additionally, the literature review revealed that convenience is one of the main orientations towards online grocery shopping (e.g. Morganosky & Cude, 2000; Ramus & Nielsen, 2005; Verhoef & Langerak, 2001; Chen & Chang, 2003) and price one of the main factors taken into consideration, both on- and off-line (e.g. POPAI, 2011; Santos, 2009). However, it was also shown that online grocery shopping is complementary to traditional grocery shopping, being preferred for non-perishable products, evidencing the still existence of some drawbacks on the adoption of this retail channel for grocery shopping (Hand, Riley, Harris, Singh & Rettie, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007). Coexisting with offline shopping, online grocery shopping is viewed in the same light, not much as a pleasure but more as a utilitarian oriented activity (Robinson, Riley, Reetie & Rolls-Willson, 2007; Verhoef & Langerak, 2001). As such, consumers are more motivated to complete the task quickly and efficiently (Robinson, Riley, Reetie & Rolls-Willson, 2007), which lead online grocery shopping trips to be considered as directed-buying store visits exhibiting goal-oriented browsing strategies (Moe, 2003). Therefore, and as suggested throughout this chapter, the consumer decision making process is influenced by consumer’s demand and pre-shopping plans and goals defined (Santos, 2009). In addition, given the precision and rationality of their purchases and their task-oriented strategies, there’s evidence that such goal-directed shoppers are less prone to impulse behaviours and deviations from plans (Moe, 2003; Wolfinbarger & Gilly, 2001). Furthermore, the relation with these shoppers and online stimuli is fickle, as the main goal is task-completion, making exploratory browsing more specifically dependent on store design (Parsons & Conroy, 2006). The relation with in-store stimuli, independently of the retail channel, was found mostly dependent on affective reactions and emotions. Moreover, on offline shopping, a lower incidence of in-store decisions was evidenced on shopping trips with more specific goals and that are part of a multistore strategy, plus evidence was found that shoppers anticipate and account for unplanned purchases in their plans (Bell, Corsten & Knox, 2011; Stilley, Inman & Wakefield, 2010; Kollat & Willett, 1967). Such results cannot, however, be extrapolated for the online retail channel so far. The full-length of these results, paired 22

with the understanding of the consumer decision making process, allowed for the elaboration of the framework depicted in Figure 2.2. This framework complements the traditional decision making process with the key factors present in the online retail channel. The emphasizes is in how pre-shopping decisions and other consumer related variables are inter-related with the buying and browsing patterns of consumers, as well as their response to stimuli, and how these interconnected and moderating factors affect online grocery consumers’ decision making processes overall. Thus, focusing on the most important aspects uncovered through this chapter, an overall view of the online grocery shopper decision making process is depicted in the conceptual framework established.

The next chapter presents the methodology developed for this dissertation, followed by the analysis of the results in Chapter 4 and the conclusion’s presentation in Chapter 5.

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CHAPTER 3: METHODOLOGY In order to address the research questions established in Chapter 1 and formulate conceptually relevant propositions on online grocery shoppers’ decision making processes, an empirical study was conducted. The following chapter describes in detail the methodological approach underlying the study’s design, implementation and subsequent analysis of results.

3.1. Research purpose and approach As stated in Chapter 1, the general aim of this dissertation is to develop, as accurately as possible, an overall image of the consumers’ decision making process for online grocery shopping. The objective is to provide a broad description of the overall process, from the pre-decisional to the post-decisional phase, however being the intent to then focus on the actual decisional stage. Within the decisional phase, two details take particular consideration – the buying/browsing strategies used by online grocery shoppers and their reaction to in-store stimuli. However, as indicated in the preceding chapters, the body of research on online grocery shopping is not particularly extensive, with the majority of studies tending to focus on the drivers of adoption of such consumption behaviour, rather than on the actual in-store decision making process of shoppers – with a few exceptions, however mostly for generalized online shopping (Moe, 2003; Demangeot and Broderick, 2006; Wolfinbarger & Gilly, 2001). As such, the appropriate method to empirically investigate the research questions established is an exploratory research approach, given that this approach is the most commonly used when there’s a need to increase or clarify the understanding of a problem. Furthermore, and as in the case of this dissertation, this type of approach is particularly useful when existing theories are insufficient or contradictory, when important concepts and its interrelationships are hard to establish and/or when an area of investigation is hard to differentiate from others (Saunders, Lewis and Thornhill, 2007).

3.2. Research strategy and design In light of the research purpose and approach underlying the development of this dissertation, a mixed methods strategy, namely a convergent parallel research design, was selected (Bryman, 2012; Creswell & Plano Clark, 2011; Tashakkori & Teddlie, 24

2003). Convergent designs are characterized by the concurrent, but independent collection and analysis of quantitative and qualitative data, with the aim of combining findings to obtain meaningful answers to the underlying research questions (Creswell & Plano Clark 2011; Bryman, 2012). For combining both qualitative and quantitative methods in several different possible ways, a mixed strategy offers many positive prospects, although not being as institutionalized as single quantitative or qualitative strategies (Bryman, 2012; Tashakkori & Teddlie, 2003). Namely, by being able to combine both elements of research, it helps to fill-in the gaps when relying solely on either one of the two methods is not optimal. As in the present study, in which neither quantitative not qualitative methods on their own would be sufficient to portray a complete and detailed picture of the overall purchase decision making process of consumers shopping online for groceries (Bryman, 2012; Tashakkori & Teddlie, 2003; Creswell & Plano Clark, 2011). Furthermore, as Bryman (2012) adds, there are several ways in which qualitative research may be helpful in guiding quantitative research, and vice-versa. For example, one of the forms in which quantitative research can possibly form ground for further qualitative research is through the selection of subjects to be interviewed or observed. At the same time, not everything a researcher needs to inquire is possible via subjects’ observation, in such case a multi-strategy approach might be undertaken as to collect the necessary information (e.g. social class backgrounds, demographic characteristics, experiences prior to the observation). In this multi-strategy design, and although is not typical (Creswell & Plano Clark, 2011), a priority is given to the qualitative collection of data and consequent analysis given that this strand better matches the requirements of the research questions defined, being the quantitative methods essentially used as in the example above (Creswell & Plano Clark, 2011; Tashakkori & Teddlie, 2003). As such, this multi-strategy approach entails a single cross-sectional web-based survey (quantitative method) - from which participants were selected, identified and profiled within the target population of online grocery shoppers, their grocery shopping and purchase patterns and their level of planning established; and semi-structured interviews paired with online grocery purchase observations and a self-administered questionnaire (qualitative methods) – as to uncover important predecisional drivers of online grocery shopping behaviour, particularly in-store buying/browsing strategies and responses to in-store stimuli, as well as relevant postdecisional outcomes of online shopping trips. All these steps will be further described in the following sections of this chapter. 25

3.3. Population and sampling Similar with the Shopping with Consumers method (Lowrey, Otnes & McGrath, 2005), and as mentioned in the previous section, shoppers were recruited via a web-based survey in which they were asked to participate in the remaining part of the study. The population of interest for the first part of the study (quantitative method of data collection) was defined as Portuguese adult online grocery shoppers (i.e. 18 years-old or older), who purchase their groceries from Continente Online and reside within the country’s geographical limits. This represents a population of approximately 80.0001 individuals (estimation based on reported data for 2010, from LINI (2010) and Dionísio, Pereira & Cardoso (2012), as no concrete data is available from the retailer in question). A convenience sampling method and snowballing technique were employed in the distribution of the survey, which was conducted via a social network and email contacts. Given the integration of social media in the survey distribution, it becomes extremely difficult to exactly determine how many people the link to the web-based questionnaire reached. Nonetheless, a rough estimated can be made, including both means of webdistribution, accounting for at least 255 individuals reached, approximately. From these, only 65 individuals started filling the survey, all of whom have completed it and were therefore valid. This corresponds to a response rate of approximately 25.5%, which is consistent with Bryman’s (2012) indication of low response rates for online surveys, which the author argues are also less significant for convenience samples. In addition, information on social media distributed surveys response rates is not yet available, which might help to explain such a low rate. After filtering the answers that fall outside of the scope of the population defined, the questionnaire contributed with a final convenience sample of 55 shoppers, which thus constituted the final sample for the quantitative study. The final sample was analysed contrasting the shopping behaviour of consumers residing within and outside the Grand Lisbon area. As the results showed no disparities, and being unpractical to conduct observations outside the city’s limits given the thesis constraints, the selection of the participants for the second part of the study was conducted based on the 38 shopper sample of Continente Online consumers residing within the Lisbon area. That is, the population of interest for the qualitative study was defined as adult online grocery shoppers (i.e., 18 years-old or above), Portuguese naturals and residents of the Lisbon area, conducting an online shopping trip 1

The approximate population is based on a 44.6% of Internet users, from which 35% purchase goods and services online, resulting in an average of 9% more frequent purchase of online groceries (LINI, 2010; Dionísio, Pereira & Cardoso, 2012), for which 55.6% of consumers show a preference for Continente Online (Dionísio, Pereira & Cardoso, 2012).

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for their household at the retailer Continente Online. Given this and assuring that these consumers met the study requirements and only participated in the study once, from the population defined, a sample of 10 willing participants was purposefully sampled and recruited to take part in semi-structured interviews and accompanied online shopping trips. The sample for the second study was determined as to guarantee a balanced and heterogeneous sample (e.g. diversity and balance in gender, age, income, shopping frequency, etc.), which profile matched the one found on the first study’s sample. Furthermore, as stated previously, individuals conducting their shopping trips in other retailers were excluded, given that the market leader was chosen as to guarantee an ease of results’ analysis and consumer grouping and comparison, as mentioned in Chapter 1. Additionally, consumers aiming at purchasing items directed at people out-side the house, re-sale or special situations (e.g., birthday party) were also excluded, as these situations did not fit the scope of the study. In the analysis of the qualitative study sample, one of the participants was not included, given incongruences with the study purpose and the individuals understanding of it and subsequent non-relying results, leaving the second study with a final sample of 9 participants. Further information on the participants’ profile is presented in the next chapter (Table 4.3).

3.4. Data collection The data collection techniques employed were based on the Shopping with Consumers method (Otnes, McGrath & Lowrey, 1995), particularly by its prior applications to the study of shopping behaviour (Demangeout and Broderick, 2006; Xia, 2010), and previous studies by the POPAI Institute (2011 and 2012), combining the advantages of previous techniques used in the study of grocery shopping behaviour. Firstly, participants were recruited and selected via a web-based survey; a pre-shopping interview, actual purchasing trip observation and post-shopping interview followed as the next three stages; the final stage entailed a self-administered questionnaire to assess psychographic characteristics not assessed so far.

Web-based questionnaire As mentioned above, the first method of data collection was an online questionnaire (depicted in Annex 1), administered via a social network and personally sent e-mails, with the aid of the Qualtrics Software during October and November 2012. This survey was elaborated according to the research questions and conceptual framework defined 27

for the study, and based on survey construction literature (Bryman, 2012; Malhotra & Birks, 2007). Its contents were divided into 4 blocks of questions about (1) online grocery shopping habits; (2) patterns of online grocery store visits and category purchases; (3) out-of-store information search and planning of online grocery store visits and (4) socio-demographic characteristics. At the end of the questionnaire, shoppers were asked if they would like to be part of the remaining part of the study, with an associated reward of a 10€ gift card. In case of an affirmative answer, the software prompted them to register an active e-mail address for further contact Consumers were only vaguely informed about the nature of the second study – “a study on the consumer’s behaviour towards online grocery shopping” – as to keep further observations with the minimum interference possible. After the elaboration of the questionnaire, a pre-test was conducted as to confirm the survey’s clarity and ease of comprehension and completion, only after which the web-based survey was launched.

Semi-structured interviews and accompanied shopping visits As mentioned, the second part of the study was comprised of 4 stages: a pre-shopping interview, accompanied shopping trip to Continente Online, a post-shopping interview and a brief self-administered questionnaire (Annex 2 depicts the script purposefully developed to guide the data collection). The items and scales present in the script were developed according to the research questions and conceptual framework and relevant literature established (Bryman, 2012; Malhotra & Birks, 2007). Moreover, the elaboration of the script of the qualitative study entailed a crucial previous analysis of the online store, as to understand the environment in which the consumer shops and how he or she might navigate the store and perform its inherent activities (Annex 3 illustrates one of the main windows of the online store in which the shopper navigates). As with the quantitative method of this study, after the interview & observation script elaboration, a pre-test was performed to insure that clarity, comprehension, ease of execution and correlation with the intended results was obtained. The qualitative study was administered according to each participant’s environment (i.e., home, office) and timing of choice (i.e., weekday vs. weekend and morning vs. afternoon vs. night) within the possibilities, this method was employed as to remain as truthful as possible to each consumer’s shopping trip planning and purchase, without interfering. Data collection took place between in the second half of November 2012, with the time expected to collect each participant’s data being the time each participant takes in their 28

purchasing experience plus an average of 20 to 30 minutes to complete the remaining steps – on average, each participant was engaged for 90 minutes in the study. The interview was performed immediately before the shopper logged-in to the retailer’s website (www.continente.pt). First, shoppers were inquired about their purchase intentions and goals for that particular store visit. Questions related to shopping intentions were carefully designed and asked, as to influence consumers’ answers the least as possible, and they were free to respond in any kind of segregation level (i.e. category, brand or product). Participants were then asked about their on- and off-line store and category purchases patterns, resources committed to that store visit and their general out-of-store planning and information search habits. Finally, consumers were asked to log-in into the website, and the observation phase was ready to begin. In this stage, there was no further interaction between the interviewer and the participant, as data was collected only through behavioural observation, being the task of the interviewer to observe without interference while taking notes of the participants’ actions. Therefore the pre-shopping interview was crucial to eliminate any possible discomfort and/or psychological barriers between both parties that could compromise the quality of the data collection. Particular attention in this stage was given to the buying/browsing strategies consumers used while shopping online for groceries, and their possible response to the stimuli present in such environment. Regarding in-store stimuli, a special single form (Annex 2 – B1) was filled at the beginning of the store visit, in case the shopper visualized any of the store’s applications and/or special promotional banners. For the remaining part of the store visit, each visit to each of the retailer’s broad categories present in the store (groceries, beverages, fresh produce, dairy, frozen foods, baby, hygiene, cleaning, home, pets, leisure, promotions, campaigns, and novelties) was recorded in a separate form (Annex 2 – B2), registering in each form the products within that category placed in the basket for each category visit. Once participants completed their online shopping trips, paid their bill and loggedout of store’s shopping page, a post-shopping interview took place to assess their overall satisfaction with the shopping trip and the online store. Prior to this, participants were also asked to provide self-reported measures of shopping trip fulfillment, unplanned buying behaviour and browsing activities. All scales (browsing activities, shopping trip satisfaction and overall store satisfaction) were scored on a 1- to 7-point strongly disagree to strongly agree scale, elaborated as a combination of previously tested and validated items (Bearden, Netemeyer & Haws, 2010; Bruner, 2009). In their 29

evaluation of the shopping trip, shoppers were also asked for a copy of the shopping receipt. To finish their participation in the study, shoppers were asked to answer a selfadministered questionnaire, in which psychographic scales were applied as to assess relevant individual characteristics – i.e., shopping styles and attitudes towards shopping. As revealed throughout the literature review, convenience (e.g. Rohm and Swaminathan’s, 2004; Morganosky & Cude, 2000; Ramus & Nielsen, 2005; Verhoef & Langerak, 2001; Robinson, Riley, Reetie & Rolls-Willson, 2007; Chen & Chang, 2003) and price sensitivity (e.g. POPAI, 2011; Santos, 2009; Sproles & Kendall, 1986) are two of the main orientations that shape the way in which consumers shop online for groceries. As Sproles & Kendall (1986) state “a consumer decision making style is defined as a mental orientation characterizing a consumer’s approach to making choices”, meaning a cognitive and affective orientation that influences and leads the consumer’s decision making process. Following the authors (Sproles & Kendall, 1986) guidelines, and after identifying the major characteristics shaping the decision making process for online grocery shopping, three scales were developed in order to measure the sample’s orientations. More specifically, and according to the literature review and conceptual framework established on Chapter 2, shoppers were evaluated on their convenience-orientation, price-sensitivity orientation and impulsiveness orientation. As in the previous stage, all scales were scored on a 1- to 7-point likert scale, where 1 equals strongly disagree and 7 equals strongly agree, being all scales elaborated as a combination of previously tested and validated items (Sproles & Kendall, 1986; Bearden, Netemeyer & Haws, 2010; Bruner, 2009). The filling-in of the selfadministered questionnaire ended the qualitative study, as the interviewer thanked the participant for their time and delivered the gift card promised.

3.5. Data analysis Web-based questionnaire The quantitative data was analysed via the SPSS Software for statistical analysis. After treating the data (i.e. correct missing or incorrect values and recoding some relevant variables), both univariate and multivariate statistical procedures were conducted as a means of analysing the data. Descriptive and frequency statistics were used to uncover the survey’s socio-demographic information and the respondents’ patterns of planning and purchase, given the separate items of the survey. Furthermore, a series of Chi30

square tests was performed as to test the dependency relation of levels of planning with other relevant variables. While analysing the connections of traditional and online stores, the product categories’ likelihood of purchase for the online environment was also analysed through a series of paired sample t-tests.

Semi-structured interviews and accompanied shopping visits Each interview was recorded on paper, transcribing the observations guided by the interview & observation script, as well as additional commentary made voluntarily by each participant. The qualitative data analysis included the following steps (Saunders, Lewis and Thornhill, 2007): (1) preliminary exploration of the data by reading through the transcribed materials, and confirming the usefulness of results; (2) elaboration of a master template for data coding and segregation, through the development of themes, based on the research questions and the data itself; (3) aggregating similar codes together into the defined themes, and verifying codes; (4) coding, segmenting and labelling of the data, per respondent, according to the master template defined; (5) connecting and interrelating themes, in a descriptive narrative, integrating each case and across-case analysis. The descriptive analysis and results’ presentation was initiated with the measurement of the participants’ shopping orientations, given their importance in framing online grocery shopping. Each scale was measured based on the mean value for the sum of the scales’ respective items, for each respondent. Thus, analysing the possibility of segregating consumers based on shopping orientations, and subsequently analysing their influence on the variables this dissertation aims to study. These variables were analysed and presented following the stages’ order of the consumer decision making process - from the pre-decisional stage, to the decisional and finally the postdecisional stage.

The next chapter presents the analysis of the data collected, by the order in which the methods were presented. That is, the results’ discussion is presented phased, given the results inherent quantitative or qualitative nature. Finally, the thesis last chapter, Chapter 5, focuses on the thesis conclusions, implications and further research.

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CHAPTER 4: RESULTS’ ANALYSIS & DISCUSSION

This chapter presents and discusses the results of the analysis of the data collected throughout all of the stages of the study described in the previous chapter. Firstly, a brief analysis of the web-based survey is presented, followed by the qualitative analysis of results. The latter begins with an analysis of consumers’ psychographic profiles, followed by the analysis of the pre-decisional, then decisional and finally postdecisional phase of the consumers’ decision making processes. This chapter culminates with the elaboration of conclusions and presentation of research propositions.

4.1. Results of the web-based questionnaire A demographic profile of the web-based survey participants is provided in Table 4.1. The average online grocery shopper respondent is a working married female, with a higher education, aged 33 years old, living in a 3-person composed household with one child and a medium to high household monthly net income. The demographics of the respondents matched very well with the profile previous online grocery shopping studies found descriptive of the largest consumer segment - highly educated females, aged 25–55 years old, with a full or a part-time job and with children under their care (KPMG International, 2012).

Table 4.1 – Demographic characteristics (n=55) Variables

Percentage Gender

Female Male

78% 22% Age

Mean ± SD

33,04 ± 10,71 Marital Status Married or Cohabiting 67% Single 29% Divorced or Separated 4% Number of People in the Household Mean ± SD 3,09 ± 1,34 Number of People in the Household under Mean ± SD 0,73 ± 0,93

Variables

Percentage

Education Secundary or Lower 24% Higher Education 76% Ocupation Student 15% Self-employed 22% Employed 60% Unemployed 4% Household Monthly Net Income Low (< 500€ - 1000€) 27% Medium (1001€ - 2000€) 35% High (2001€ – > 4000€) 38%

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As per the participants’ online grocery shopping patterns, regarding preferences at the moment of purchase, results show that the majority of consumers shop online for groceries less than once a month (56%), and for those who shop more regularly, once a month represents the main frequency of purchase (31%). The high percentage of infrequent purchases might reveal that online grocery shopping is still not well disseminated amongst consumers, being still an infant retail format for this type of shopping, as several studies indicate (KPMG International, 2012; Lim, Widdows & Hooker, 2009; Ramus & Nielsen, 2005). On the other hand, it might also be an indication of Hand, Riley, Harris, Singh & Rettie’s (2009) results, that this type of purchase is highly dependent on the existence of temporarily circumstantial situations. Additional, the monthly frequency of purchase, for more regular shoppers, might represent evidence that online grocery shopping trips are mostly considered as major shopping trips. However, as the reasoning of the shoppers’ purchase frequency was not the aim of this study, further research should be provided on these conclusions. Furthermore, overall results revealed that most shoppers prefer to shop during weekdays (44%), although one third of respondents revealed not having a specific preference for the day of the week. Moreover, for those who shop during the week, the preferred schedule is at night/after work (59%), while those who shop during the weekend are equally indifferent between the timing of the day they shop (morning, afternoon or night time). Finally, online grocery shoppers have a distinct preference for shopping alone (86%), at home (87%) and using their personal computers (93%). Although representing a small piece of evidence, it’s worth mentioning that from the consumers who tend to shop with company, 70% choose to shop with their spouse or partner. The marked preference for shopping from home and in a personal computer contrasts the results of previous studies (KPMG International, 2012) that indicate evidence of a growing preference for mobile technologies while online shopping, which might indicate that the average Portuguese consumer has yet to fully acquire the technological trends of other worldwide shoppers. Table 4.2 includes descriptors of the participants’ online grocery shopping planning patterns. The great majority of respondents declared having some degree of planning regarding online grocery shopping (89%). These specific respondents (n=49) show a general use of a paper shopping list, which the shopper elaborates primarily alone and mostly during the day of the purchase, and mostly without pre-establishing a monetary 33

or timely budget. Regarding the search for promotions, offers and discounts, only 11% of respondents claimed to pay zero attention to this type of information, while 36% declared to only pay some attention to this type of information while in-store and most respondents (53%) claimed to have a moderate to high level of attention and/or search for such information prior to purchase. In addition, Chi-square analyses were performed to identify variables significantly related to the respondents’ level of planning. Only the search & attention to promotional activity and shopping list usage were found to be significantly related to the level of planning (respectively: Chi-square=15.551, p=0.016; Chi-square=24.975, p=0.000). The use of a shopping list and attention to offers and deals allows consumers to be more focused and better express their shopping intentions (Deloitte & Harrison Group, 2010; POPAI, 2011), as such, given that the level of planning represents the level of stated purchase intentions prior to purchase, it is easy to conclude that the more effort put into these activities will result in a higher level of stated intentions and goals. Additionally, from those respondents who declared a high level of planning, the majority (86%) writes a detailed paper shopping list and shows a medium level of search and attention (48%). While, most informants who declared medium levels of planning either use a partial written list (45%) or just a memory list (35%), and only pay attention to promotional activities directly sent by the retailer (55%). In addition, half of those who show the lowest levels of planning, exhibit zero interest in promotional information (50%). None of the demographic variables showed significant results in relation to the level of planning, although having children, for example, could be expected to have a significant relation. One possible reason for this result is the overall change in consumer habits, in the mist of the current economic conditions. As most shoppers are becoming more focused and rational about their shopping trips making use of several tools to better plan and purchase, across and within consumer segments (Deloitte & Harrison Group, 2010; POPAI, 2011). The high level of planned intentions, control features and deal proneness can be seen as a reflection of the new grocery shopper habits evidenced in previous studies (Deloitte & Harrison Group, 2010; POPAI, 2011). Which naturally should translate to online retail, as this is often seen as another tool to reduce costs and increase convenience and control over shopping (KPMG International, 2012; Nielsen, 2009; Verhoef & Langerak, 2001).

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Table 4.2 – Planning patterns (n=49) Variables

Percentage

Shopping List Written (Total or Parcial) 82% Memory 16% Other (Electronic List) 2% Timing of Planning A few days before purchase 37% During the day of the purchase 41% Immediatly before purchasing 22% Alone vs. Accompanied Planning Alone 55% With Company 45%

Variables

Percentage

Pre-established Monetary Budget No 69% Yes 31% Mean ± SD €87,27 ± €51,01 (excluding outliers)

Pre-established Timely Budget No 82% Yes 18% Mean ± SD (N.A=2) 31,43min ± 13,45min

Regarding store choice patterns between online and traditional stores, all respondents claimed to purchase their groceries in traditional stores alongside the referred online retailer. This results is congruent with past studies (Hand, Riley, Harris, Singh & Rettie, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007), which suggest that online grocery shopping is complementary to instead of a substitute of traditional shopping. The main reason respondents’ stated for having chosen Continente Online as their online grocery retailer is the fact that they already shopped in the retailer’s traditional stores. This might help explain the fact that, in regards to single preferred traditional store, Continente is the most referred brand (53%), followed by Pingo Doce (47%). In addition, 70% of informants claimed to shop at more than one traditional store, with 20% of shoppers claiming to shop solely at both Continente & Pingo Doce, and 40% claiming to shop at the previous combination of stores plus another brand (the main stores added to the previous combination are Lidl at 56% and Minipreço at 25%). Given the complementarity of traditional and online stores, the type of product categories most purchased online was analysed, performing paired sample t-tests on the average likelihood of purchase for all major product categories2. Results showed that there are no statistically significant differences between the Groceries, Dairy, Beverages, Cleaning and Hygiene product categories, but that all these categories show statistically significant differences (p<0.01) in regards to all other categories (Meat, Fish, Fruit, Vegetables, Baked Goods, Deli and Frozen Foods). Furthermore, within the latter group, Meat & Fish, Fruits, Vegetables & Baked Goods and Deli & Frozen Foods showed no statistically significant differences within each group, but showing statistically significant differences (p<0.01) between groups. As such, the product 2

Only major categories were included in the test, as these are certainly present in stores of all types, sizes and retail formats, decreasing a possible sample bias.

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categories most purchased online are Groceries, Dairy, Beverages, Cleaning and Hygiene, followed by Deli & Frozen Foods, then Fruits, Vegetables & Baked Goods and finally Meat & Fish. A result congruent with previous studies, which stated that the categories with the lowest likelihoods of purchase are the categories representing perishable or sensitive products, for which consumers’ still demonstrate uncertainty in buying online (Hand, Riley, Harris, Singh & Rettie, 2009; Robinson, Riley, Reetie & Rolls-Willson, 2007).

4.2. Results from the semi-structured interviews and accompanied shopping visits As mentioned in the previous chapter, the analysis of the qualitative study findings was initiated with a psychographic analysis of the respondents’ profiles (Table 4.3), according to their shopping orientations which were measured based on the mean value of the sum of each scale’s respective items and characterized on a ‘high’ or ‘low’ basis3. As a result of this analysis, it was possible to sort consumers into different groups. Given the generalized low results for the impulsiveness orientation, these groups were defined solely based on the ‘high’ or ‘low’ labels for each of the two remaining orientations. Table 4.3 – Respondents’ profiles Shopping Orientations Scales's Results

Name

Gender

Age

Marina

Female

20s

Low

Low

High

Hélia

Female

20s

High

Low

Low

Ana

Female

late 30s

High

High

Low

João

Male

50s

High

High

Low

Tiago

Male

30s

High

High

Low

Sofia

Female

late 20s

High

Low

Low

Paula

Female

late 30s

High

High

Low

Luís

Male

20s

High

Low

Low

Vera

Female

40s

High

High

Low

Convenience Price-Sensitivity Impulsiveness

Description Studying full-time, living with husband, with medium level household income Studying full-time, living with partner, with low level household income Working full-time, living with one child, with high level household income Working from home, living with wife and adult daugther, with medium level household income Working full-time, living with wife and one child, with medium level household income Working full-time, living with husband and one child, with medium level household income Working full-time, living with partner and two children, with high level household income Working full-time, living with mother, with medium level household income Working full-time, living with partner and two children, with a medium level household income

3

All scales were scored on a 1- to 7-point likert scale, from strongly disagree to strongly agree respectively, being all scales elaborated as a combination of previously tested and validated items (Sproles & Kendall, 1986; Bearden, Netemeyer & Haws, 2010; Bruner, 2009). Given the intermediate characteristic of the 4-point scale within the 1- to 7-point likert scale, all total scale scores that average between 4 and 4.5-points are considered low values, and those between 4.5 and 5-points are considered high values.

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From the sample collected, 2 main groups arose: (1) the high convenience and high price-sensitivity group (from now on labeled type A), formed by Ana, João, Tiago, Paula and Vera; and (2) the high convenience and low price-sensitivity group (from now on labeled type B) formed by Hélia, Sofia and Luís. The ‘low convenience’ groups were the ones for which it was expected to be none or very few respondents allocated, given the major convenience feature of online grocery stores (e.g. Morganosky & Cude, 2000; Ramus & Nielsen, 2005; Verhoef & Langerak, 2001; Nielsen, 2009). As such, the ‘low convenience, low price-sensitivity’ group will receive a minor focus on this analysis, as results can be biased due to the single-respondent allocation (for the same reason, no label is needed for this group, being solely mentioned as Marina). It’s relevant to mention that, within the high convenience and high price-sensitivity group, there’s a distinction between informants – as Ana, Tiago and Vera show a higher score for the convenience orientation versus the price-sensitivity orientation, while João and Paula show the opposite. The resulting allocation of respondents to different groups allowed for the qualitative analysis of the remaining variables observed during the field study, aiming at studying the differences and similarities between groups, while answering the research questions and drawing meaningful propositions.

4.2.1. Pre-decisional phase As described in the preceding chapters, for the purpose of this study and within the predecisional phase of the consumer decision making process, the variables in analysis are included in two major parts of this phase: the planning phase, in which consumers plan their purchases, goals and purchasing conditions (such as, location, means, and other variables); and the inter- and intra-purchase cycles, in which the frequency of purchase in the online and offline stores is defined, as well as the differences in both types of purchases.

Planning In general, the planning characteristics analysed in this study show overall similarities between and within groups, as well as compared with the results of the previous study. Regarding shopping lists, all consumers declared to have a shopping list with most or almost all the products that were intended to be purchased, except for Marina which showed more relaxed intentions. There’s no shown preference for the type of shopping 37

list, being this is equally divided between paper, memory and a combination of paper lists with the store’s electronic list application. Most consumers elaborate their shopping plans with the other members of the household, except for those who shop accompanied by the spouse, for which the shopping list seems to be elaborated more individually. Regarding the attention and search of promotional activities before the shopping trip, none of the consumers declared a high degree of attention or search. Nonetheless, Marina showed the most attention to this type of information, contrasting with the majority of respondents. As type A consumers presented limited or moderate attention, while type B consumers declared not to be motivated to process or pay attention to such information. Finally, regarding the timing chosen for shopping, given the diverse characteristics of consumers, this variable shows a higher degree of variation which might be primarily influenced by consumers’ lifestyles and should be subject to further studies. Nonetheless, the combination between the day of the week and the period of the day preferred is ‘during the weekend, in the afternoon’ and ‘during week days, at night or after work’. Major similarities are also apparent within and across all consumer types, regarding the preference for shopping at home, in a personal computer and alone (however confirming their purchases with the remaining members of the household before finalizing the shopping trip), and owning the store’s loyalty card.

Inter- & Intra-Purchase Cycles As with the planning characteristics, the results show major similarities within and across all consumer types, as well as the results from the previous study, in what concerns the purchase cycles between different stores and within the online store in question. All consumers, with no exceptions, declared additionally shopping for groceries at least at one traditional store. Defining the purchase elaborated in the online store as a major shopping trip, and the purchase elaborated in traditional stores as a fillin shopping trip. The concrete definitions of both types of trips are hard to define, as the frequency of shopping somewhat varies between consumers – Marina, Hélia, Sofia, and Vera declared shopping online for groceries once a month, while Tiago, Ana and Luís declared shopping twice a month and only João and Paula declared a somewhat more weekly online purchase. Nonetheless, based on the shopping intentions and goals verbalized by respondents, a major shopping trip was defined as a less frequent larger purchase, with a wider variety of products chosen both for semi-immediate 38

consumption and/or stocking. While a fill-in shopping trip was described as a somewhat more frequent (daily or weekly) smaller purchase directed towards the reinforcement of the pantry, during the time-lag between major shopping trips. These definitions coincide with the work of previous studies (Kollat & Willett, 1967; Bell, Corsten & Knox, 2011). Another major similarity between consumers is the difference in the type of product categories acquired in both types of trips and stores, and the traditional stores preferred. The main difference between stores is the choice of traditional stores for the purchase of perishables, meaning fresh products such as meat, fish, bread, fruit and vegetables, as consumers showed an elevated level of aversion in purchasing this type of products online. Alongside fresh foods, consumers also tend to choose traditional stores to purchase dairies with a lower time span of consumption (e.g. milk and yogurts). Regarding store choice, although some consumers also choose to purchase at other stores (e.g. traditional Continente stores, farmers’ market), the primary store mentioned is Pingo Doce.

4.2.2. Decisional phase Buying and browsing strategies The analysis of the strategies used while shopping presented distinct results between groups and across type A respondents, and seem to be a reflection of the consumers’ orientation towards price. In type A consumers, the distinction is present between the already mentioned two groups, (1) João and Paula (referred from here on as type A1), and (2) Ana, Tiago and Vera (referred from here on as type A2). Type A1 consumers show high value scores for convenience, low scores for impulsiveness and the highest value scores for price-sensitivity which surpass that of convenience. This type of consumers showed a shopping strategy more focused on the purchase of the intended items, at the best possible price. The search for products is slightly slower, as to guarantee that the correct products are placed in the shopping basket and there are no ‘best deals’ missed. With this intent, consumers searched for products through each product category section and sub-section, which allowed consumers to be organized fulfilling the goal expressed above, and only after entering each sub-section consumers went directly to the product desired. The choice of product seemed essentially derived from price, as stated, as consumers heavily compared products characteristics versus price. Further from the in-the-moment comparison, respondents had previous 39

knowledge of each product’s price, from previous purchases and/or comparison of prices between stores. In the pursuit of their goals, type A1 consumers generally give a final look at all product categories’ sections before finalizing their purchases, as to guarantee they don’t miss any wanted products. At the same time, while shopping, these consumers somewhat control their spending, although the main control is done at the end before the final purchase confirmation. One interesting fact that João showed, was the lower level of price comparisons in the Beauty & Hygiene and Cleaning categories, which are categories generally with more expensive items – this difference seemed explained, at least to some extent, by revealed brand effects. Some of the consumers’ statements4 during the respective shopping trip that validate their shopping orientations were: “I want this product, because I know it’s good and it’s the cheapest one”, Paula “I’ll take this one, because I know it’s also good and the second cheapest”, Paula, when confronted with the failure of search of the private label product she was looking for. “No, I don’t want this product because it’s cheaper at Pingo Doce”, João

On the other hand, type A2 consumers also show high scores for convenience and pricesensitivity, however, the latter are not as high as in the previous group making the convenience scores surpass price-sensitivity. This type of consumers shows some preoccupation with price, although their orientation towards convenience reveals itself more prominent. Their strategy is more direct and more focused on task completion than the previous type of consumers, being the goal the efficient conclusion of the chore of grocery shopping. Type A2 consumers use primarily the ‘direct search’ option, searching for each product by the order they appear on the shopping list. After getting the results for each search, consumers go directly to the product they want and/or are more familiar with, however showing an average moderate level of price comparison. Furthermore, there’s evidence of strong brand effects throughout most product categories. However, the level of price comparison is more salient in the Beauty & Hygiene and Cleaning categories, contrasting to that found on type A1 consumers. Furthermore, neither the amount nor time spent on the task seemed to be controlled during the shopping trip, like consumers A1 the majority of the control was done before the purchase final approval. Likewise, both types of consumers only seemed to search 4

Statements were translated from Portuguese, reflecting exactly the meaning expressed by consumers.

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for products’ additional information when they felt the need to clarify any doubts related with the product. Here are some of the statements4, type A2 consumers mentioned during their shopping trips, and that reflect their shopping choices: “I’m choosing this one, because from the brands I like, it’s the cheapest”, Vera “I’m not choosing this one (cheapest product), because I prefer that brand”, Vera “I prefer to stock on some items, so I don’t have to buy them so often”, Tiago “I’m choosing this one because it’s the one my kid likes”, Ana & Vera

Type B consumers are somewhat of a variation of type A2’s strategy, marked by the surpassing of the price-sensitivity scores by the convenience scores. Essentially, most elements are the same or very similar, however what distinguishes the two is the extent of the price-sensitivity orientation. Type B consumers present a high score for convenience, however a low score for price-sensitivity, as well as a low score of impulsiveness. Nonetheless, similar to type A2 consumers’ strategy, these respondents look for the efficient and direct purchase, as to waste the minimum time possible in the task. Either from using the ‘direct search’ tool or making use of each category’s section (both search methods were present in the sample, showing the same outcomes), type B consumers go directly to the product or brand they desire without wasting too much time in price or product comparisons. The most comparisons occur in less habitual purchased products or categories, where brand and/or product choice are less defined – which coincided mostly with the Fresh Foods and Dairies categories. Furthermore, the search for additional product information, as with the remaining consumer types, occurred only to clear some doubts related to a product or to place a product in the ‘favourite’ selection. As per the spending control during the shopping trip, it seemed of a minimum level, except for categories in which products are more expensive and/or the total spent on the category was higher than that of other categories. However, the main point of control, as with the other consumer types, occurred at the end of purchase before final confirmation. Here are some of the statements4, type B consumers mentioned during their shopping trips, and that reflect their shopping choices: “As I still have some budget left, I usually take another look at the product categories to see what else I can still get, that I feel like buying”, Hélia “I don’t like to waste much time on this, I quickly choose the products I know I need and in several units, so I don’t have to purchase them so often”, Luís

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“I look for price, but usually only in products I’m more indifferent to. For a lot of products I prefer specific brands”, Sofia

Finally, Marina’s strategy reveals the most differences versus the other consumer types, revealing low levels for price-sensitivity and convenience, and a contrasting high level of impulsiveness. These differences reside essentially on the level of focus of the shopping trip and the level of price comparisons. Marina showed a more unfocused strategy, very calmly analysing each product category section and sub-section to verify what products she needed, without engaging in a lot of product comparisons or budget control, and choosing mainly national more expensive brands. The following statement4 depicts her strategy. “I like to see every section and look for what I want, and I’m an advocate of national brands which I always choose”, Marina.

Response to Stimuli For the purpose of analysing responses to stimuli, three types of stimuli were paid attention to. In terms of design and interactivity, it’s safe to say that all consumers showed ease and comfort in shopping online for groceries in this specific store. However, the search, use and fluency within the website were obviously very conditioned by its design and interactivity level. Not only were shoppers conditioned by the available types of search, but also by the location of each search tool and the organization of the information within each search tool. As well as by the location of, for example, the delivery schedule, which many consumers damned unfit in the beginning, and therefore opted by only choosing their delivery schedule at the end of their purchase. Ultimately, the design and interactivity of the online store reflected a negative response on consumers, as several issues with failed search terms, poor information organization and terrible page loading and website connectivity were accounted for. As for actual point-of-purchase stimuli, meaning product advertising (mostly appearing in the form of banners) and store applications, the response from consumers is similarly negative. All consumers showed and overall dislike for product advertising during their shopping trips (except for Marina), irresponsiveness to the retailer’s general website and its applications, and general disregard for the promotions, offers or discount campaigns sections present inside the online store (only type A1 42

consumers showed some kind of receptivity to these sections). Finally, with regards to impulsiveness and unpredicted stimuli, consumers’ response is as well negative. As stated previously, and confirmed by shopping trip results, impulsiveness levels of all consumers except Marina are low, being the completion of planned goals the most declared reason for finishing a shopping trip. Unpredicted stimuli appeared in the form of failed searches and loading issues, for which shoppers showed little patience – as for the searches, after only a few attempts, most shoppers ended up giving up on the product they were searching for. Regarding website loading issues, several consumers complained of this as a recurring problem which very negatively influences their shopping and willingness to shop – João, for example, experienced such website connectivity issues that he contemplated terminating the shopping trip.

4.2.3. Post-decisional phase The data collected provided overall similar results between consumers, both within and between groups, with few significant variations present. In general, the method of payment preferred is by debit card at the time of delivery – consumers expressed feeling less risk by using this method. The amount of products not purchased is very small, and in several shopping trips even inexistent, being the main reasons for forgoing a purchase: the fact that the product is cheaper in other stores, failure to find the product, problems with the search results and substitute purchases. As per the products that were in fact purchased, however were not planned, results show low levels of unplanned products for all consumers, except for Marina. In this sense, unplanned purchases were defined as all the products consumers did not show intention of purchasing (i.e. either by the shopping list or during the pre-shopping interview), which reflects the definition established in previous studies (Inman, Winer & Ferraro, 2009). Cross-checking the information provided by consumers during the first interview (shopping intentions), the information provided in the second interview (shopping goals not met) and the final shopping receipt, it was possible to analyse unplanned purchases. Results revealed that online grocery shoppers spend more on planned products than unplanned products and that unplanned purchases are fairly low, being mostly represented by items forgotten during planning and substitute purchases. Moreover, all consumers declared to have navigated the online store as usual, and only search for the product categories in which a product was desired (being Marina an exception for the latter). This result, paired with 43

the complementarity of retail channels’ result, might be an indication of Bell, Corsten & Knox’s (2011) finding that on a multi-store strategy there are less unplanned purchases, due to the more specifically defined purchase goals. In terms of consumer satisfaction with the online store and the shopping trip, results present an average high level of trip and store satisfaction, displaying a low average level of browsing. A low level of browsing activity means that consumers spent more time searching and purchasing intended items, than looking for what products to purchase or even just browsing for fun. Marina shows, to no surprise, the highest level of browsing, which is aligned with her high level of impulsiveness and unplanned purchases. This result might reflect the attribution of a higher hedonic value to online grocery shopping, focusing more on satisfaction than task completion and showing low involvement towards this type of purchase. Thus, Marina contrasts with the remaining respondents, who embody low impulsiveness, low levels of unplanned purchases, low levels of browsing and an orientation towards task completion; showing the attribution of a higher utilitarian value to online grocery shopping, and a high level of involvement. Although grocery shopping is considered a habitual purchase, which would be considered more of a less involved purchase, most consumers showed an increased level of rational decision making in their shopping trips which reflects high involvement and is an example of the complexity of this type of shopping (Solomon, Bamossy, Askegaard, & Hogg, 2006). Finally, regarding consumer satisfaction, although visit and store satisfaction present a high average score, several consumers expressed their unpleasantness with a few of the stores attributes. As mentioned before, the primary causes for consumer unpleasantness are relate to the organization of information, ease of use of the online store, website loading issues and, additionally, the low level of promotions and discounts offered.

4.3. Resulting propositions The analysis of results permitted the retrieval of meaningful content, which in turn can be summarized in the following propositions to guide future studies. Proposition 1: online grocery shoppers will be persuaded mainly by utilitarian motivations, being the shopping trips goal-directed, meaning oriented towards efficient task completion and goal achievement. However, these buying strategies are likely to vary, at least, according to consumers’ convenience and price-sensitivity orientations.

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Proposition 2: varying on consumers’ impulsiveness, online grocery shoppers will exhibit low levels of deviations from planned shopping, low levels of browsing with no specific purchase intention and little response to in-store advertising stimuli; while exhibiting a strong response to the design of the online store platform, in what enables consumers to more efficiently achieve their goals. Proposition 3: some resistance towards online grocery shopping is still found within Portuguese shoppers, as a whole and towards the online purchasing of fresh produce specifically. Thus, the different channels in grocery shopping are used complementarily, being online grocery shopping used primarily for major shopping trips and traditional shopping (mostly smaller stores, such as supermarkets) used primarily for fill-in trips. Proposition 4: online grocery shoppers’ patterns’ profiles are proposed similar, however, still showing lower levels of technology use and trustworthiness in online shopping compared with previous studied online grocery shopper populations. In addition, it is proposed that the high levels of planning and control showed by respondents can be a reflection of the new grocery shopper habits, evidenced in previous studies for traditional grocery shopping, across retail formats.

The preceding analysis enabled the exploration of the themes and variables relevant for the writing of this dissertation, as expressed in previous chapters. Moreover, it helped to define online grocery shopping related propositions aimed at future research. As such, in concluding this dissertation, the following chapter will elaborate on the study’s conclusions, implications and managerial suggestions, and finally, research limitations and future research.

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CHAPTER 5: CONCLUSIONS

After analysing the data collected, it is imperative to theoretically conclude on the relevant findings, as well as their respective implications for the industry and body of academic research in question. Moreover, this chapter presents the limitations found within this study and guidelines for future research.

5.1. Conclusions & Suggestions The first conclusion this study provides is the realization of online grocery shopping in Portugal as being a niche market. Although being generally well accepted throughout the world as a form of grocery shopping, with a retail business growing each year, (e.g. Lim, Widdows & Hooker, 2009; Hand, Riley, Harris, Singh & Rettie, 2009), during the execution of the methodology much difficulty was found in reaching actual online grocery shoppers, as the low survey response rate demonstrated. The latter could possibly be due to the general lack of interest of the targeted respondents on the study, the inappropriate method of survey distribution, or the actual low number of online grocery shoppers. Despite the publically announced high number of consumer registrations to the two main online grocery stores (Acepi, 2011), which can be assumed as revealing consumers’ intentions to try out or search more information related to this type of purchase, no official numbers of actual purchases were found in the market and the estimate for Continente Online presented in this study (LINI, 2010; Dionísio, Pereira & Cardoso, 2012) was found to be far lower from the announced number of registered clients. Furthermore, from the sample that was possible of being collected, almost 60% of shoppers claim to shop online for groceries less than once a month. Moreover, all consumers from the sample collected declared shopping for groceries in other traditional stores and showed high levels of aversion towards the purchase of several product categories. Given these facts and the ad-hoc consumer information collected during the process of this study, it can be suggested that online grocery shopping in Portugal is still a developing market facing several market penetrating issues. Nonetheless, through the elaboration of this research, it was possible to gather information regarding the overall decision making process of online grocery shoppers, which, as mentioned, has seldom been the focus of previous research. In general, results revealed high levels of similarities between consumers, which is congruent with a small 46

niche market. Moreover, regarding pre-decisional factors, and although results cannot be generalized, both studies uncovered similar results for the average shopper planning patterns, which further reinforces the previous point. As per the overall decision making process, this was generally found to be a rational process with utilitarian motivations, following defined planning and purchasing patterns established from previous shopping trips. Furthermore, the study of consumer shopping orientations allowed for the definition of different consumer groups, based on the main orientations framing online grocery shopping (e.g., Morganosky & Cude, 2000; Ramus & Nielsen, 2005; Verhoef & Langerak, 2001; POPAI, 2011) – price-sensitivity and convenience. Consumer types within which, it was possible to analyse different decision making variables, according to the defined research questions, leading to the conclusion of the existence of different browsing and purchasing strategies. Two main strategies were found to exist, which vary essentially in the difference between the level of convenience and price-sensitivity orientations. Consumers, who declared a higher degree of price-sensitivity over convenience, showed a more price focused strategy (type A1 consumers). While, consumers who declared a higher degree of convenience over price-sensitivity orientations presented a higher degree of focus towards task completion, rather than price. Two types of consumers were included in this last group, one type of consumers showing high price-sensitivity and high convenience orientations (type A2 consumers), and another group declaring also high convenience, but low price-sensitivity scores (type B consumers). In this sense, what distinguishes type A2 from type B consumers is the different level of price orientation (e.g. deal proneness, price comparisons), while remaining similar through the crucial focus on convenience. However, through consumer observation, it was uncovered that other consumer orientations (i.e. brand and quality orientations) might also be affecting the way consumers shop online for groceries, more specifically affecting product choice and product comparisons made. These new found orientations seem to affect mostly type A2 and B consumers; however, this observation deserves further research. By further analysing all consumer types found, it is also suggested that overall online grocery shoppers present negative responses to all types of in-store stimuli. The analysis revealed low levels of attention and willingness to process advertising and in-store promotional activity, low levels of experimental browsing and low levels of unplanned purchases. In addition, consumers showed some concerns regarding the store’s web connectivity and overall design. Thus, it is important, especially from the retailers’ perspective, to notice the results of 47

consumers’ evaluations and feedback. Most consumers showed satisfaction with their shopping trip and with some aspects of the online store (such as, product variety and delivery service). However, most consumers also expressed their unpleasantness regarding connectivity and page loading – several complained about the excessive waste of time derived from these issues, and some also forgone purchases due to them. Moreover, most consumers declared disliking the way in which the information is organized and presented within the online store, expressing some product search issues as well – once again, some consumers ended up forgoing purchases due to the failure of product search results. Finally, while showing depreciation towards product advertising while shopping, most consumers showed some degree of dissatisfaction regarding the level of product promotions and discounts. Given all the feedback collected, and through the analysis of both the retailers online store and other online grocery stores (national and international stores), it’s fair to say that online grocery stores in Portugal still have some way to go before locking in consumers’ loyalty, satisfaction and frequent repeated purchases.

Managerial suggestions The above conclusions suggest that Portuguese retailers should maybe rethink their online store image and organization; reflect on what consumers actually desire, and what would satisfy them the most, and thus produce higher store visits and consequently higher sales. Regarding the retailer Continente Online, one suggestion would be firstly to obliviously correct the loading and connectivity issues presented. Furthermore, information organization and search results tools should be reconsidered, as the more intuitive an online store is, the easier it will be for consumers to understand it and choose to purchase. The online store has an overcomplicated information organization system, and an outdated, and sometimes even pointless, direct search tool. Moreover, most items are repeated throughout several categories’ sub-divisions, which seemed to confuse consumers. Additionally, another of the most unpleasant variables present during shopping is product advertising – the online store presents an exaggerated level of advertising banners throughout product categories, which only reflects too much noise during purchases and don’t engage consumers, for which the retailer should rethink alternatives. Other suggestions that could improve the overall store image and consumer store satisfaction would be to: improve products’ additional information, 48

adding for example composition and/or nutritional information; change the location of suggested items (which currently appear at the end of the page of each product’s additional information), as most consumers very rarely check products’ additional information and as they usually don’t scroll down to the end of the page, suggested items aren’t even acknowledged; at least, translate the online store website to English, given the multicultural characteristic of cosmopolitan cities, such as Lisbon and Oporto; change the filtering options within each category section (e.g. as the United Kingdom’s online store Tesco, which seems much more intuitive and easy to use – Annex 4); and finally, to analyse the possibility of other search tools (also as an example from Tesco, the multi-search tool where consumers can search several products at one time – Annex 4). Besides the implications for retailers, the conclusions revealed through this research have also indicated several references for future research.

5.2. Limitations As most exploratory studies, this investigation is not without its limitations. As a study based on a non-probability sample, generalizations to other audiences may not be appropriate. As such, a larger sample size would be advised as to confirm the results obtained, for example, as to more accurately profile the average consumer and/or the distinct groups found based on browsing and shopping strategies. Other limitations arise from the dissertation’s timely and budget restrictions, namely the focus on one single retailer and one single shopping trip. As to best confirm the results obtained, and to possibly generalize results at a population level, the ideal scenario would be to analyse the three existing online retailers through multiple shopping trips over time. In this sense, it is possible to conclude similarities and differences between and within consumer groups, and between shopping trips – as to verify if consumer’s profiles are the same between retailers or if there are significant differences, and if shopping trips’ characteristics are similar over time. Another limitation to this study is the method used for data collection. Although showed valid and reliable for the purpose of this study, the method utilized still leaves margin for some loss of information. In this sense, it would be preferred, and even more reliable, to use a combination of video recording and a computer-tracking tool. As to guarantee that all information is kept for analysis, particularly information not easily understood at the moment of information collection. Additionally, the method of survey distribution might also represent a limitation for the 49

study, as no proof could be found if this was or not related with the difficulty in encountering online grocery shoppers and low response rates. A possible solution for this problem, in future studies, can be to partner with the retailer in question, as to have access to an appropriate sampling frame of online grocery shoppers.

5.3. Future Research Regarding future research in this field of study, it would be beneficial, both in a managerial and academic perspective, to conduct a similar study correcting the methods of data collection to the ones explained above, and increasing the sample size. Moreover, given the characteristics of Portuguese online grocery shoppers previously presented, it would be relevant to analyse the actual receptivity and acceptance of this type of purchase, and the variables influencing present outcomes. Furthermore, and as new influential shopping orientations were discovered, it would be interesting to analyse additional consumer shopping orientations, and the respective interactions between orientations, in consumers’ strategies and profiles. Additionally, after possibly generalizing results to a population level, it would be pertinent to contrast consumer characteristics, decision making processes and styles between online grocery shopping and offline grocery shopping. Finally, given the consumer feedback received, it would be important, at a managerial level, to thoroughly analyse the current online store website and possible alternatives and changes. To realize how, for this particular type of purchase and retail industry, specific website construction variables influence consumers’ decisions; and which variables, and respective levels, would better engage consumers, consequently increasing loyalty, engagement and sales.

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ANNEX 1 – Web-based questionnaire for online grocery shopping5

Com que frequência faz compras de supermercado ONLINE?

Em que altura costuma fazer as suas compras ONLINE?

Várias vezes por semana; 1 vez por semana De 2 em 2 semanas; 1 vez por mês; Menos de 1 vez por mês

Durante a semana; Ao fim-de-semana De manhã; À tarde; À noite/depois do trabalho

Em que local costuma fazer as suas compras ONLINE?

Faz normalmente as suas compras ONLINE

Em casa; No escritório; Nos transportes; No trânsito; Outro

Sózinho; Acompanhado (por quem?)

Que meio utiliza para fazer as suas compras ONLINE?

Em que cadeia ONLINE costuma fazer as suas compras ?

PC; Telemóvel/Smartphone; Tablet; Outro

Continente Online; Jumbo Online; El Corte Inglés Online; Outro

Qual a principal razão para fazer compras nessa cadeia?

Em que cadeias TRADICIONAIS também faz compras?

Fazia compras nas lojas tradicionais da mesma cadeia; Maior e melhor variedade de produtos; Boa experiência de compra ao utilizador; Bom serviço de entrega ao domicílio; Bom serviço de atendimento ao cliente; Melhores preços e promoções; Por recomendação; Outra

Continente; Jumbo; Pingo Doce; El Corte Inglés; Intermarché; Lidl; Minipreço; Só faço compras de supermercado em lojas online; Outra

Que tipo de produtos costuma comprar ONLINE? 1 = nunca compro a 5 = compro sempre

Dispõe habitualmente de informação promocional antes de iniciar as suas compras ONLINE?

Mercearias, Carne (Talho), Peixe (Peixaria), Fruta, Legumes, Lacticínios, Padaria e/ou Pastelaria, Charcutaria (Queijos, Carnes Frias, Enchidos), Bebidas (sumos, águas, refrigerantes, cervejas), Produtos de garrafeira (vinhos, aguardentes, espumantes, bebidas espirituosas), Congelados, Refeições pré-cozinhadas, Produtos Gourmet, Produtos de Alimentação Especial (Dieta, Alimentação Infantil), Produtos de limpeza e drogaria, Produtos de beleza e de higiene pessoal, Alimentação e outros produtos para Animais

Procuro activamente através de campanhas promocionais que aparecem nos media e/ou perguntando a familiares e amigos; Presto alguma atenção à informação promocional que as cadeias de supermercados online me enviam diretamente; Não, limito-me a prestar alguma atenção à informação promocional que aparece no website da loja online Não, porque nunca tenho grande interesse nesse tipo de informação.

Costuma planear antecipadamente que produtos comprar ONLINE?

Como é que planeia aquilo que vai comprar ONLINE?

Tudo ou quase tudo o que vou comprar; Apenas parte do que vou comprar, o resto decido à medida que vou fazendo as compras; Não, decido tudo ou quase tudo à medida que vou fazendo as compras.

Lista de compras escrita, detalhando tudo ou quase tudo o que pretendo comprar; Lista de compras escrita, detalhando parte dos produtos que quero comprar; Não faço nenhuma lista de compras escrita, sei de memória o que é que quero; Outro.

Quando costuma planear aquilo que vai comprar na loja ONLINE?

Planeia sozinho aquilo que vai comprar ONLINE?

Alguns dias antes; No próprio dia; Imediatamente antes de fazer as compras

Sim; Com o meu cônjuge; Com o meu cônjuge e os meus filhos; Com os meus filhos; Com os meus pais e/ou irmã(os); Com as pessoas com quem partilho casa; Outro

Estipula habitualmente um montante máximo para gastar nas suas compras ONLINE? Quanto?

Estipula habitualmente um período máximo de tempo para gastar nas suas compras de ONLINE? Quanto?

Qual é o seu género?

Qual é o seu ano de nascimento?

Qual é o seu estado civil?

Tem filhos?Quantos? De que idade (s)?

Quantas pessoas tem o seu agregado familiar?

Quantos elementos do seu agregado familiar têm < de 18 anos?

Por favor indique as suas habilitações literárias:

Por favor indique a sua principal ocupação:

Por favor indique o rendimento líquido mensal do seu agregado familiar?

Estaria disposto a participar neste estudo de mercado?Email?

5

The table presented is a representation only of the web-based survey, as a means of conveying the type of questions asked. The original survey was complete and well presented as to promote the maximum number of complete surveys.

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ANNEX 2 – Script for the semi-structured interviews and observation of shopping trip6

A – ENTREVISTA PRÉ-VISITA DE COMPRAS: 1.a). Vai fazer as suas compras online com o auxílio de uma lista de compras escrita? 1.b). Pode por favor discriminar o que vem comprar hoje a este supermercado? 1.c). É só isso que precisa? É tudo o que vem comprar? Não se lembra de mais nada? Não vem comprar mais nada? 2. Que tipo de compra é que estes produtos representam? 3. Costuma fazer compras noutro supermercado/hipermercado, seja online ou tradicional? Qual/Quais? 4. Que tipo de compras costuma fazer nesse(s) supermercados/hipermercados? 5. Tem conhecimento de algum produto ou marca que esteja hoje em promoção aqui na loja Online? Quais? 6. Como teve conhecimento dessa promoção? 7. Quanto dinheiro estima vir hoje gastar em compras? 8. Quanto tempo estima vir hoje gastar nas compras? 9. Com que frequência faz compras nesta loja? E quando foi a última vez que visitou esta loja online para efectuar compras?

B – OBSERVAÇÃO DA VISITA DE COMPRAS: B1. O Início da Visita (PREENCHIMENTO ÚNICO POR VISITA) Hora de entrada no website? Hora do login? 1.Após entrar no website do Continente, efectuou directamente o login? 2.O que observou anteriormente à compra? 2.1.Adicionou artigos à lista de compras/carrinho com base nos destaques/aplicações observadas? Após efectuar o login.......? 3.Uso de ‘lista de compras’ online? 3.1.Visualizou alguma Informação? 3.1.1Adicionou artigos à lista de compras/carrinho com base nas secções observadas? 4.Marcou imediatamente o período de entrega?

6

The table presented is a representation only of the script that guided the qualitative collection of data, as a means of conveying the type of questions asked. The original script was complete and well presented as to promote the most efficient data collection.

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B2. A Compra: (FICHA REPETIDA – CADA SECÇÃO = 1 FICHA) Categoria? Produtos Adquiridos? Hora de entrada na categoria?

7.Foi interrompido por alguém enquanto visitava a secção?

1. O consumidor iniciou a busca do artigo, através de que secção?

7.1.Alterou o seu comportamento de compra com base nessa interrupção?

2.Após entrar na categoria do produto, o que fez?

8.O consumidor substituiu algum produto, APÓS o ter colocado no carrinho de compras?

3.Ao procurar o artigo, o consumidor pesquisou informação adicional sobre o mesmo ou produtos concorrentes?

9.O participante mostrou estar a contabilizar o montante/tempo/nº de items?

4.Ao procurar o artigo, o consumidor alterou a apresentação e a ordenação da listagem de produtos?

10.Após terminada a visita a esta secção, o participante terminou as suas compras? Porquê?

5.O consumidor visualizou alguma publicidade enquanto visitava a categoria?

11.Qual o meio de pagamento utilizado?

6.Comprou algum item devido a essa publicidade?

Hora de saída da secção? Hora de término das compras? Hora de pagamento/saída da Loja Online?

C. ENTREVISTA PÓS-VISITA DE COMPRAS: 1.Das coisas que tinha planeado inicialmente levar, houve alguma que tivesse acabado por não comprar? Quais e porquê? 2.E comprou algumas coisas que não tinha inicialmente pensado em comprar? Quais e porquê? Pedir para recolher a lista de compras escrita (ou uma cópia) e o recibo de compra. 3.Hoje navegou através do site da loja como habitualmente o faz? Se não, porquê? 4.E passou apenas nos separadores em que sabia que queria comprar algo ou percorreu também outros separadores? Porquê? 5.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):  Passei uma grande parte da visita à loja online a procurar e a pensar sobre os produtos que haveria de comprar.  Durante o tempo que estive na loja online concentrei-me essencialmente em encontrar e colocar no carrinho os produtos que tinha planeado comprar.  Perdi mais tempo do que esperava a tentar decidir que produtos comprar.  Considero que a visualização de promoções, catálogos e novidades durante as compras online me ajudou bastante a decidir que produtos comprar.  Enquanto fazia as minhas compras tentei não desviar a minha atenção do que estava a fazer, de forma a não perder tempo.

6.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):           

Fazer compras online hoje foi muito agradável. Fazer compras online hoje foi muito divertido. Fazer compras online hoje foi muito útil. Fazer compras online hoje foi muito cansativo. Fazer compras online hoje foi muito dispendioso. Fazer compras online hoje foi muito demorado. A visita de compras online de hoje correu como eu tinha esperado. Fiquei satisfeito/a com o resultado final das minhas compras online de hoje. Durante a visita de compras online de hoje consegui comprar tudo o que precisava. A presença de publicidade durante a visita de compras online de hoje tornou-a mais agradável. Aconteceu-me hoje continuar a fazer compras online não tanto porque precisava de comprar mais coisas, mas porque me apeteceu.  Durante as compras online de hoje, entretive-me bastante a procurar e a pesquisar os vários produtos disponíveis.  Durante as compras online de hoje, tentei focar-me ao máximo em fazer as compras que precisava, de modo a não gastar demasiado tempo nem energia com esta actividade.

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7.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):          

A loja que visitei online tem uma imagem moderna e apelativa. É fácil encontrar aquilo que procuro na loja online visitada. A informação na loja online está bem organizada. A loja online visitada tem uma boa oferta de promoções e descontos. A loja online visitada é de fácil utilização. Sinto que a minha informação pessoal está bem protegida quando uso esta loja online. Normalmente, o tempo de espera pelas entregas desta loja online corresponde ao prometido. Normalmente, os produtos entregues por esta loja correspondem ao que foi comprado online. A loja online visitada tem um bom sortido de produtos. A loja online visitada tem um bom nível de preços.

D. QUESTIONÁRIO INDIVIDUAL: 1.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):     

Geralmente faço compras de supermercado por impulso. Muitas vezes faço compras de supermercado sem pensar. Faço compras de supermercado de acordo com o meu estado de espírito no momento. Pondero bem as minhas necessidades antes de fazer uma compra no supermercado. Consigo normalmente resistir à tentação de comprar coisas a mais no supermercado para não ultrapassar o meu orçamento.  Quando vejo algo que realmente me interessa no supermercado, compro sem pensar muito nas consequências.  Apenas compro algo no supermercado quando estou certo/a que vale o dinheiro gasto. 2.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):  No supermercado, comparo geralmente os preços das diversas marcas para garantir que consigo o melhor produto ao preço mais acessível.  No supermercado, compro normalmente mais depressa marcas que estejam em promoção ou com desconto do que as restantes.  Sou capaz de visitar vários supermercados para ter a certeza que vou comprar os produtos que quero ao melhor preço.  No supermercado, opto geralmente por comprar marcas ou produtos com preços mais acessíveis.  No supermercado, tenho por regra verificar atentamente os preços dos produtos que estou a comprar, mesmo daqueles que normalmente são dos mais baratos.  Presto bastante atenção aos vários descontos, promoções ou baixas de preço que vão sendo oferecidos pelos supermercados onde habitualmente faço compras. 3.Diga em que medida concorda com as seguintes afirmações (sendo 1 = discordo totalmente e 7 = concordo totalmente):  Não gosto de gastar muito tempo a procurar informação adicional sobre os produtos que tenciono comprar no supermercado.  Não gosto de complicar a ida às compras de supermercado.  É-me muito conveniente fazer compras de supermercado sem sair de casa.  Não gosto de esperar em filas de supermercado para pagar ou levantar as minhas compras.  É muito importante para mim não perder tempo quando vou às compras ao supermercado.  Gosto de poder fazer compras de supermercado de forma rápida e fácil, e a qualquer hora do dia, através da Internet.

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ANNEX 3 – Continente Online Store Layout7

ANNEX 4 – Tesco’s Store Layout with ‘multisearch’ tool8

7 8

http://www.continente.pt/HomePage.aspx http://www.tesco.com/groceries/

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Online Grocery Shopping:

Master in Business Administration - Major in Marketing Online Grocery Shopping: An exploratory study of consumer decision making processes JOANA MAR...

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