Excerpt
Table of Contents
Abstract
List of Figures
1Introduction, aims & objectives
1.1 Introduction
1.2 Aims and objectives
2Literature review
2.1 Location-based marketing
2.2 Consumer decision-making process
2.3 Stimulus organism response model
2.4 Influences on consumer behaviour
2.4.1 Cultural factors
2.4.2 Social factors
2.4.3 Personal factors
2.4.4 Psychological factors
2.5 Types of buying behaviour
2.5.1 Complex buying behaviour
2.5.2Dissonance-reducing behaviour
2.5.3Habitual buying behaviour
2.5.4Variety-seeking buying behaviour
2.6Types of shopper
3 Research questions and hypotheses 33
4 Methodology and data collection
4.1 Methodological approach
4.2 Sampling approach and data collection
5 Data analysis and results
5.1 Sample size characteristics
5.2 Characteristics users vs. non-users
5.3 Stimulus organism response model
5.4Mobile advertisement
5.5 Mobile advertisement–Hypotheses testing
5.5.1Hypothesis – Lifestyle orientation
5.5.2 Hypothesis – Price sensibility
5.5.3 Operating system – Price sensibility
5.6 Respondents’ involvement – Hypotheses testing
5.6.1 Hypothesis – Information gathering
5.6.2 Hypothesis – Purchase across-channels
5.7 Behaviour change by shopping apps
6Conclusions and recommendations
7 List of Appendices
8 Bibliography
Abstract
Consumers’ environment has always been influencing consumers’ decision-making processes. With the end of the seller dominated marketing approach and the rise of a customer orientated marketing approach, at the end of the 1960’s, the significance of marketing communication increased, in order to inform consumers and to establish a customer relationship. The dissemination of new technologies and innovations such as colour television, home computer and the internet has contributed to an increasing benefit for consumers and organizations. Consumers’ choices increased in terms of product variety and hence the complexity of consumers’ decision-making processes rose. Therefore, it has been ever since relevant for marketers to analyse and evaluate consumers’ decision-making processes and consumers’ behaviour. With the evolution and diffusion from mobile phones to smart phones a new horizon for consumers opened and a new dimension to mobile devices added, consisting of the accessibility and availability of information regardless location and time. Consequently, consumers’ decision-making processes have been influenced and the relevancy of mobile-location based marketing and related services for consumers and organizations increased.
The present master dissertation constitutes on the increasing importance of mobile location-based marketing and services. The objective is to investigate the impact of location-based services on consumers’ buying behaviour which is significantly impacted by consumer-decision making processes. Therefore, relevant theoretical models and theories concerning consumers’ decision-making process and buying behaviour are described and evaluated. Furthermore, primary data is collected via online questionnaires and face-to-face interviews, in order to conduct an empirical analysis. The results reveal that consumers’ requirements, towards mobile-location based marketing including location-based services such as shopping apps and mobile advertisement, are segmented. It is identified that technology affine consumers are more likely to purchase across-channels. Further, these consumers show a higher acceptance of stimuli conveyed by mobile advertisement. Personal and psychological factors such as price sensibility, lifestyle orientation and consumers’ involvement are identified as impacting factors on consumers’ decision-making process within this research.
List of Figures
Figure 1 Mobile devices: Daily screen use vs. media spend in 2013
Figure 2 Process of technology innovations and technology adoption curve
Figure 3 Consumer decision-making process
Figure 4 Stimulus organism response model
Figure 5 Top 3 influencing factors at each stage of consumer decision
Figure 6 Life cycle stages
Figure 7 Maslow’s hierarchy of needs
Figure 8 Revised pyramid of needs
Figure 9 Continuum of Consumer Buying Decision
Figure 10 Four types of buying behaviour
Figure 11 Key Shopper Factors
Figure 12 Distribution age group and number of shopping apps
Figure 13 Chi-Square Test – Age group / number of shopping apps
Figure 14 Moments when shopping related apps are used
Figure 15 Distribution Users vs. Non-Users – Shopping related purposes
Figure 16 Distribution of users and non-users among age groups
Figure 17 Chi Square Test – Recommendation by friends & shopping apps
Figure 18 Evaluation information channel (purchase online – users vs. non-users)
Figure 19 Mean analysis – Evaluation responding factors
Figure 20 Mean analysis – Evaluation responding factors (users and non-users)
Figure 21 Perception of mobile advertisement
Figure 22 Evaluation mobile advertisement: users and non-user
Figure 23 Correlation analyses: Users and non-users concerning lifestyle
Figure 24 Distribution operating systems among users and non-users
Figure 25 Correlation analyses: Android / iOS users and price sensitivity
1 Introduction, aims & objectives
The following chapter provides an introduction to this master dissertation’s topic, followed by the definition of the aims of and objectives of this research.
1.1 Introduction
Within the last decade the rise of mobile technologies and mobile applications have had a significant impact on internet information search, data accessibility and availability. The increasing number of enthusiast consumers using their mobile phones for purposes far beyond personal communication represents a high potential advertising market and emerging communication channel (Taylor et. al. 2011:2). When Apple Inc. launched in 2007 the first iPhone it revolutionised not only communication technology by the new design and features, but also a new generation of new mobile applications. Other global players such as Google, Microsoft and Blackberry followed Apple by introducing their own app stores. Consequently, the competition increased and consumers’ choice between the available software programmes has already a significant impact on consumers’ future decision-making processes, in terms of purchase places such as Apple’s App Store and Android’s Play Store.
Four major value-added services categories resulting from the evolution of mobile technologies and mobile applications occurred and consist of information, communication, transaction and entertainment (Kuo et. al. 2009; 887). The increasing importance and the high economic potential of the mobile economy has a significant impact on organizations marketing strategy and customer relationship management due to the fact that organizations can interact with their customers along the relationship cycle (Aiello 2014; 226). Organizations can tailor and customize product offers based on customer data, in order to attract customers and to retain a long lasting customer relationship. By building a lasting customer relationship superior customer value and satisfaction have to be created due to the fact that satisfied customers are more likely to be loyal customers (Kotler & Armstrong, 2012; 34). Customers’ perceived value results from the differences between customers’ perceived benefits in terms of economic, functional and psychological, and the required invested resources from customers’ perspective consisting of monetary, time, effort and psychological in order to receive those benefits (Schiffman et. al, 2008). Customers’ perceived value is relative and subjective, thus the identification and the increase of customers’ perceived value represent a major challenge for marketers in order to understand and predict consumer’s behaviour.
Mobile technologies and mobile applications have changed organizations’ consumer interaction. It also changed and extended consumers options due to information search, data accessibility and availability. The related functions of mobile apps concerning time- and location-sensitive properties can be referred to ubiquity (Okazaki & Mendez, 2013; 98), whereby ubiquity can be defined as the accessibility of information which is not related to time and place anymore. The benefits result from users’ flexibility, which is based on users’ determination when to receive, respond or to take advantage of location-specific promotions (Okazaki et. al.2012; 170). Thus, consumers’ involvement is potentially influenced by the possibility to access information independent from place and time which in return has an impact on consumers’ decision-making processes.
1.2 Research objectives
The primary objective is to identify the influence of shopping apps and mobile location-based marketing on consumers’ buying behaviour. Consequently, it is essential to differentiate respondents to mobile location-based marketing within the scope of the differentiation between users and non-users of shopping apps. The importance of mobile devices as mobile advertising and shopping app carrier will be therefore examined.
The secondary research objective consists of the determination of consumers’ involvement along the decision-making process with focus on users and non-users of shopping apps. Furthermore, it is crucial to differentiate if information is gathered actively in order to determine consumers’ involvement within the decision-making process. Hence, consumers’ needs and wants when using shopping apps respectively when responding to mobile location-based marketing is identified. Further, the usage rate of shopping apps is evaluated and determined. For that reason mobile-location services are classified within the adoption of innovation curve. Besides, it will be clarified if users of shopping apps are in general more likely to research product related information compared to non-users of shopping apps.
The differences between users and non-users in terms of their information gathering activities will be underlined to provide further information and evidence regarding consumers’ involvement along the decision-making process. The most impacting communication channels which lead to a purchase in-store or online are identified concerning users and non-users. The objective is to determine technology affinities concerning users and non-users. Additionally, consumers’ impacting factors such as a psychological and personal are impacting consumers’ decision-making process. Because of the fact that these are varying and impacting consumers’ decision-making individually it is different to detect those ones. Nevertheless, the personal factors such as price sensibility, affinity to new technologies and lifestyle-orientation are examined regarding users and non-users of shopping apps in order to illustrate underlying personal and psychological factors and their influence on consumers’ decision-making process.
The tertiary research objective focuses on the determination of the main product categories for information gathering activities and / or product purchases conducted by consumers on their mainly used mobile device. In combination with the previous research objective regarding the identification of consumers’ needs and wants it provides a holistic research approach to determine the key factors for organizations to attract new potential customers.
Further, the characteristic differences between users and non-users are determined to prove that services within the scope of mobile-location based marketing are confronted with fragmented needs and wants of users and non-users of shopping apps. The potential of prospective future users of mobile location-based service is defined, regarding the considered sample size and exemplified by the considered and researched German market.
2 Literature review
The following chapter provides information concerning the relevant theoretical background in order to retain a holistic approach for this research.
2.1 Location-based marketing
“Location-based marketing is a form of marketing in which marketing messages are delivered directly to a user who is within broadcast range.” (Krum, 2010; 116) Salz and Moranz explicit underline that location-based marketing closes the gap between social media, internet, out-of-home and real-life interaction as different form of mobile marketing (Salz & Moranz, 2013; 178). The network coverage for mobile internet and the increasing number of smartphone users ( Cf. Appendix 1 / 2) accesing mobile websites when they are on the go, contributed to the importance for organizations to develop and provide consumers with location-based services and mobile advertising. A study conducted by Millward Brown revealed that globaly 47% of daily screen time is spend on mobile devices including smartphones and tablets, on a global scale only 4% of global media spendings is assigned to mobile devices. Thus, the gap reveals a large potential for media advertiseres and businesses on mobile devices (Dever, 2013).
The following illustrations show the allocation of daily screen time and global media spendings.
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Figure 1 Mobile devices: Daily screen use vs. media spend in 2013
(Source: Dever, 2013)
The principle of location-based services and related mobile applications is to provide users with actual information and services around their location. This ranges from information concerning places such as Google Maps through to geosocial networks such as Foursquare. Foursquare users can login in at certain locations such as listed organizations on Foursquare and share their location with friends, in order to find out who is nearby and is interested in meeting somewhere. Moreover, users are informed about discounts, great deals and new shop openings around their location (Cf. Appendix 3). Salz and Moranz describe, that the majority of in-store app users use barcode scanning apps but social, reward and shopping apps such as Facebook place, Foursquare and Groupon play a significant role. This results from the simplification of shopping and price comparissions for the purpose of saving money (Salz & Moranz, 2013; 134). From a marketing perspective location-aware apps provide a major opportunity resulting from the fact that promotion and advertising is send in real-time to users, who are located nearby and which can be tailored to their individual needs and wants (Ryan & Calvin, 2012; 225). Therfore, impulse purchases can be initiated by informing consumers about discounts and promotions. Location-based advertising represents a major opportunity to approach customers. On the one hand through push services by informing users at their physical locations and on the other hand through pull services which “[..] might include a location based banner ad in a smart phone application that can encourage [..] to find out local store / entertainment-type information.” (De Kare-Silver, 2011; 44). According to Cunnigham et al., location- based advertising and the implied factors of location-sensitiveness, time-sensitiveness and user’s profile enable organizations to convey their added value to users. In the best case, location-based advertising is perceived as benneficial messages, instead as annoying advertising (Cunningham et al., 2004; 148). A research by Millward Brown reveals that German consumers favour advertisments less on tablets and mobile phones (combined 20%) compared to advertisements on TV and Laptops (combined 29%) (Dever, 2013). Consumers’ perception of location-based advertising and their concerns such as privacy and annoying advertising can lead to refusing location-based services.
The theoretical framework of consumer adoption of technology innovations suchs as location-based services shows that consumers pass through different stages, when confronted with new innovations such as location-based services (Roberts & Zahay, 2013; 441).
The illustrations below emphasises the consumer adoption process of technology innovations (a) and the technology adoption curve (b).
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Figure 2 Process of technology innovations and technology adoption curve
(Source: Roberts & Zahay, 2013; 441)
The stage of internalization plays a key role for complex innovations because of consumers required willingness towards a continuous learning process. The technology adoption curve clarifies that firstly innovators enter the market, driven by the motivation to experience new technologies at first. After that the early adopters follow who are interested in future applications and potential benefits. Only if certain adoption chasms such as price are bettered, the early majority adopts new technologies, followed by the late majority. Laggards are the last group of customers who are likely to be technophobic (Hill & Jones, 2009; 194). In 2011, a research by bynd revealed that 17% of US users account to early adopters in terms of social location apps (bynd, 2011). Later adoption researchers are not available concerning certain countries but globally the usage of mobile location-services is expected to soar as estimated by Cisco (Cf. Appendix 4). Shah vice president of marketing and business development at Polaris Wireless emphasises that advanced smartphone and GPS devices will lead to the adoption of location-based services by the mass market (Butcher, 2011).
2.2 Consumer decision-making process
Consumer behaviour concepts are based on other complex scientific disciplines from the field of studies of psychology, sociology, social psychology, anthropology and economics. Consumer behaviour and decision-making are interdisciplinary and are likely to be influenced by external and internal factors (Schiffmann et al., 2008; 15). Consumer’s processing of stimuli and the influences on the decision-making process are explained in detail in the subsequent subchapter 2.2 and 2.3.
Consumer decision-making process is a cognitive five sequiential stage process consisting of problem recognition, information search, evaluation of alternatives, purchase and post-purchase evaluation ( Dibb & Simkin, 2013; 125).
The following graphic shows the five sequential stages which form the consumer decision-making process.
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Figure 3 Consumer decision-making process
(Source: Liu, 2007; 15)
The consumer decision-making process starts with the recognition of a problem, respectively the identification of a need and wants. The discrepancy between the status quo and a desired state, which can be achieved through purchasing certain products or services from consumers’ point of view, plays a significant role for the initiation of consumer’s decision-making process. Marketers differentiate between assortment depletion, whereby consumers feel the need to replace products and assortment extension which defines consumer’s need to add new products to their assortment possessions. These needs can be categorised in utilitarian or hedonic needs. Utilitarian needs refer to product functionality whereby hedonic needs refer to pleasurable and / or aesthetics product attributes (Blythe,2005; 45).The problem recognition stage is triggered by a stimuli influenced by consumer’s environment. Dibb and Simkin explain the speed of recognizing a problem varies based on the consumer as individual and the way in which a certain need recognition was initiated (Dibb & Simkin, 2013; 127). After a consumer passed through the problem recognition state and identified a certain need the stage of information search starts. Within the scope of information search consumers benefit from internal or external information search. Internal search refers to consumers’ memory resulting from previous experiences or learnings. External search refers to consumers’ communication with friends and reviewing external information resources as the internet, newspapers or magazines. Resulting from this stage is a list of products also knows as evoked set that consumers consider selecting, in terms of fulfilling their previously detected need. Afterwards, consumers begin to evaluate their evoked set concerning certain requirements and criteria, and consumers assign certain importance levels to each criteria respectively requirements. Dibb and Simkin describe this process as salience and it depends on consumer’s individual criteria assessment (Dibb & Simkin, 2013; 128). Blythe emphasises, that consumers use cut-offs, in order to form a product consideration set by defining minimum and maximum acceptable values in terms of product characteristics (Blythe, 2005; 47). After consumers completed this stage by identifying a certain product for purchase, consumers purchase the certain product. “If the choice is not as clear cut as this, the consumer may have to prioritise the criteria further, perhaps by deciding that price or convenience is the one overriding factor.” (Brassington & Pettitt, 2007;75). The post-purchase evaluation stage determines if the purchase was successful or not. The evaluation within the scope of equitable performance, ideal performance and expected performance might lead to post-purchase dissonance or post-purchase consonance. Post-purchase dissonance occurs, when the expectations are not met and consumers are not satisfied, whereby post-purchase consonance describes a satisfaction resulting from exceeding product expectations (Blythe, 2013; 49). According to Lamb et al., consumers try to justify their decisions by researching new product information to support their purchase decision described as “mystic tanning” (Lamb et al., 2013; 78). Blythe adds the dimensions of reducing the importance of the issue, concentrating on the positive product attributes and distorting the dissonant information by emphasising low price and quality ratio (Blythe, 2013; 49).
2.3 Stimulus organism response model
The stimulus organism response model also known as input process output model is an advanced model of stimulus response model designed by Donald Hebb in 1955 and has been used in order to explain animal and human behaviour. Hebb considers within his approach the involvement of cognitive processes. Therefore, the individual responses vary and dependent on the perception of different stimuli (Cziko, 2000).
The following graphic illustrates the stimulus response model and the sequences of the three major steps.
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Figure 4 Stimulus organism response model
(Source: Lantos, 2011)
Stimulus factors refer to marketing stimuli and environmental stimuli, with which consumers are confronted, consist of organizations’ marketing mix and economic, technological, political and cultural factors. Marketing stimuli can be controlled by marketers whereby the control of environmental stimuli is far beyond marketers’ control (Sandhusen, p.218). Psychologists refer organism to consumer, respectively to all living creatures (Lantos, 2011; 314). Within the scope of different researches, researchers refer organism to buyer’s black box. The processes within buyer’s black box consist of buyer characteristics and psychological influences, which have a major impact on the decision-making process (Soundarapandia, 2002; 200). In contrast to Lantos’ approach, Soundarapandia, Kotler and Armstrong (Kotler & Armstrong, 2008; 122) define the major factors of buyer’s black box as buyer characteristics and buyer decision process. Lantos emphasises the significance of psychological influences on the decision-making process. Lantos, argues that reviewing different psychological perspectives on a given concept should be seen as complementary and not competing (Lantos, 2011; 316)
Therefore, Lantos states that psychological influences are impacted by consumer’s mental stage, behavioural variables and how consumers act (Lantos, 2011; 313). Buyer characteristics have a major impact on how buyers will react, whereby buyer’s decision process influences the outcome (Soundarapandia, 2002; 200). Behaviour and responses from individual are analysed in order to draw conclusion about the cognitive processes within buyer’s black box, because the cognitive processes haven’t been clearly identified (Blythe, 2013; 134 & Fifield, 1998; 120). Environmental factors within the scope of the stimulus stage impact processes and characteristics within buyer’s black box which consequently influence buyer’s responses in terms of product choice, brand choice, dealer choice, purchasing time and purchase amount (Kotler & Armstrong, 2008; 122).
It’s unlikely that consumers pass through the different stages of the stimulus organism response model every time being confronted with new stimuli. Former stimuli-response associations might result in retroactive interference in case new responses to stimuli are learned or if prior learning can be connected with new learning referring to proactive interference (Solomom et al. 2006 ;78). Learning refers to the changes of an individual’s behaviour resulting from experiences (Kotler & Armstrong, 2008; 136) Solomon describes, that an interference effect occurs over the time under the assumption that consumers learn and adopt a range of new responses and therefore the stimulus effectiveness decreases in obtaining the former response (Solomom et al. 2006 ;78). “These interferences effects help to explain problems in remembering brand information. Consumers tend to organize attribute information by brand.” (Solomom et al. 2006 ;78)
2.4 Influences on consumer behaviour
Along the decision-making process, consumers are influenced by cultural, social, personal, psychological factors which have an impact on the outcome of consumer’s decision-making process.
2.4.1 Cultural factors
Cultural norms and values, which are established within societies, impact consumer behaviour are one of the most widely environmental factors (Batra & Kazmi, 2008; 248). In order to provide a general framework for the identification and definition of culture, it is defined as a set of shared, learned, symbolic system of values, beliefs and attitudes that forms and impacts perception and behaviour (Noel, 2009; 15).
For marketers it is crucial to identify and understand cultural factors, due to the fact that these factors have an impact on whether a product or service is chosen among competitors’ or not. Marketers are trying to detect cultural shifts in order to identify new products that might be wanted (Kotler & Armstrong, 2008; 123). Besides the major shared norms and values within a culture, a culture consists of different subcultures. These subcultures are formed by a group of people who have common values based on common life experiences and situations. Furthermore, a subculture provides a psychological source of group identification and members are set apart from other society members, due to their different values and beliefs (Sumathi & Saravanavel, 2008; 521) (Tyagi & Kumar, 2004; 88). Besides that, belonging to a subculture influences consumers’ lifestyle and consumption decisions. Thus, consumer’s individual self-concept is impacted and influences brand preferences, choices, purchases and uses (Bouchet et al., 2013; 77).
The evolution of mobile services has contributed to the creation of a subculture that requires the adaptation of websites to their needs and wants (Dawson, 2012). Social classes affect also consumers’ behaviour, due to lifestyle differences. This is measured based on the combination of income, occupation, education and wealth (Kotler & Armstrong, 2008; 126).
2.4.2 Social factors
Reference groups, family, roles and status form social factors and affect consumers’ behaviour. The arise of online social networks have increased the importance of word of mouth by adding a new dimension to the existing dimension of word of mouth consisting of families, friends, clubs, internet forums and neighbourhoods (Kumar, 2009; 241). Word of mouth can be defined as the process of individuals sharing information with others in form of verbal communication e.g. face-to-face, phone and the internet (Hawkins et al., 2010; 272). Bughin identified word of mouth as primary factor, which precedes in 20-50 % of all purchasing decisions cases and has a high significance for consumers in case of first time purchasing decisions and relatively expensive purchases (Bughin et al., 2010). The following illustration shows the importance word of mouth in developing markets compared to mature markets, illustrated by the example of mobile phones and three different stages during the consumer decision-making process.
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Figure 5 Top 3 influencing factors at each stage of consumer decision journey whether a product is considered illustrated by mobile phone example
(Source: Bughin et al., 2010)
Word of mouth has a higher significance in developing markets compared to mature markets. A study conducted in the United Kingdom emphasises Bughin’s findings and reveals that consumers are more likely to feel comfortable about a company by referring to friend’s recommendation (71%) as information source, followed by ‘past experiences’ (63%) and ‘advertising’ (15%) (Schiffmann et al., 2008; 423). Within the scope of a research concerning the effect of internet word of mouth on consumers’ decision making process, researchers identified five major impacts. Firstly, internet word of mouth initiates the decision making process by being informed about new products. Secondly, information provided from online consumers’ reviews might terminate the decision-making process. Thirdly, broadening the consideration set by reviewing online reviews. Fourthly, narrowing the consideration set based on online consumer information. Fifthly, focus on new attributes which have to be taken into consideration at the alternative-evaluation stage of consumers’ decision-making process (Haugtvedt et al., 2005; 51).
Reference groups as well as opinion leaders have the ability to influence the opinion of others. Opinion leaders influence the actions and affect the attitudes of opinion seekers who are aiming to reduce the perceived risk primarily in consumer goods and services which are intangible (Kamesh, 2008; 155). Early adopters are more likely to be opinion leaders compared to innovators whose actions and behaviour initiate a diffusion process which is very efficient and effective, due to the fact that many early adopters play a significant role in their communication structures. Early adopters are individuals who adopt a product early in its life cycle. Thus, innovations can spread within a social system very quickly (Simons-Morton et al., 2012; 191) (Lamb et al., 2012; 374).
2.4.3 Personal factors
Consumers’ decisions are affected by a set of personal characteristics, which compose of buyer’s age, life cycle stage, occupation, economic situation, lifestyle, personality and self-concept (Sarangapani, 2009; 14) (Kotler & Armstrong, 2008; 123). Over the time consumers’ buyer patterns changes regarding products and services. This is induced due to consumers’ aging and consumers’ shift within the life cycle stage and results in changing needs and wants. Consumers’ lifestyle, values, environment, hobbies and consumer habit evolve (Perreau, 2013). According to Govindarajan, the major benefit of consumers’ life cycle stage is the understanding of decisions made at each life cycle stage as consumers’ pace the life cycle stages of children, subteens, teenager, single adults, young adults, middle years, maturity and senior citizens (Govindarajan, 2007; 106). This theoretical framework has to be expanded by taking a detailed perspective of the life cycle stage into consideration in order to illustrate the significance of consumers’ life cycle stage on the consumers’ economic situation.
The following graphic clarifies possible consumers’ evolving life cycle stages.
Figure 6 Life cycle stages
illustration not visible in this excerpt
(Source: consumerpsychologist.com)
The life cycle theorem of consumption and savings concerning consumption behaviour developed by Nobel Prize winner Franco Modigliani in economics, clarifies the changes in consumption patterns resulting from a change in income. While consumers pass through the different life cycle stages the income increases and consequently consumers’ consumption spending raises. Modigliani describes, that the marginal propensity to consume (MPC) shifts during consumers’ life cycle mainly in the three stages of young adult, middle age, close and in retirement. Consumers who are at the beginning of their life cycle (young single, single parent, young couple & blended) purchase products and services mainly for the first time, consequently the MPC narrows. The MPC for consumers in their middle age (full nest, blended & empty nest) increases due to the increasing income. Consumers who are close to retirement or in retirement (empty nest & older single) are more likely to experience a decreasing MPC, resulting from decreasing income and the assumption that consumers are more likely to retain their previous lifestyle (Gottheil, 2012; Pressmann, 2014; Riley,2012).
Kotler and Armstrong define lifestyle as “…a person’s pattern of living as expressed in his or her activities, interests and opinions.” (Kotler & Armstrong, 2008; 132). Consumers’ lifestyle has a major impact on the decision-making process because it determines where, when and what is consumed. Therefore, consumers have a consciousness for their lifestyle. Consumers from different cultural backgrounds, social classes or disposable income levels have different lifestyle patterns. For marketers of premium and luxury products it is further essential to identify different lifestyle patterns and target the most suitable one, due to the fact that markets shift from a product-based consideration towards lifestyle consideration, which provides consumers with a lifestyle experience (Michman, 2006; 104). Within the scope of digital lifestyle, smartphones play a significant role as primary communication and information device. Croslin emphasises, that the impact of smartphones on consumers’ lifestyle priorities is huge and the perceived value and benefit exceeds the purchase price from consumers’ point of view (Croslin, 2010). Personality and self-concept have a further impact on consumers buying behaviour and decision-making process. Personality is defined as set of unique psychological characteristics and lead to persistent respondents to one’s own environment. Marketers use the personality and self-concept approach, in order to segment consumers into different socio-cultural types (Schiffman et al., 2008; 140). Within this context marketers are aiming to design a brand’s personality to reflect its target group’s personality in order to achieve a greater brand perception among competitors. “Western global companies want to inject personality characteristics and values that are consistent across target groups [..], although in some cases marketers vary these characteristics by target group.” (de Mooji, 2010; 278).
2.4.4 Psychological factors
Motivation, perception, learning, beliefs and attitudes are the main psychological factors that influence consumers’ buying behaviour. Solomon et al. emphasise that motivation is the process that occurs to satisfy a need and the achievement of this need might be related to a functional or practical benefit (Solomon, 2010; 177). Motivation is a dynamic construct and underlies changes related to life experiences. Ernest Dichter, a psychologist and marketing expert designed one of the first methodologies in order to identify consumers’ motivation and underlying needs. Dichter identified that irrational factors have often a higher impact on the decision-making process compared to rational factors. Dichter argues, that it is crucial to identify these factors for consumers’ benefit for the purpose of a consumer driven innovation process (Dichter, 2004; 15-19). Consumer behaviourists differentiate between rational motives and emotional motives. Emotional motives are personal respectively subjective for instance pride, affection or status (Schiffman et al.,2008; 112) Identifying consumers’ motivation represents a major challenge due to the determination of irrational influencing factors and the fact that “…motivation operates below the subconsciousnes level, and in other cases it is because the person is not willing to admit to a particular motivation.” (Blythe, 2013; 47). Maslow’s approach within the context of hierarchy of needs explains the reason why individuals are driven by certain needs and motives at particular times.
The following graphic illustrates Maslow’s hierarchy of needs.
Figure 7 Maslow’s hierarchy of needs
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Maslow’s hierarchy of needs explains that a person’s needs are hierarchal segmented starting with the most important need at the bottom to the least pressing at the top. According to Maslow a person starts to satisfy their needs at the bottom and continues to the top if one need is satisfied. Kotler a Armstrong emphasises that, “… starving people (psychological need) will not take an interest in the latest happening in the art world (self-actualization), nor in how they are seen or esteemed by others (social or esteem needs), nor even in whether they are breathing clean air (safety needs)” (Kotler & Armstrong, 2008; 135). Psychologists expanded Maslow’s hierarchy of needs, resulting from the lack of supportive empirical researches and results from later conducted researches in the areas of neuroscience, psychology and anthropology. The revised pyramid of needs excludes self-actualization needs as described by Maslow, in terms of striving for status. Instead psychologist introduced parenting, mate retention and mate acquisition. Consequently, building and retaining friendships, and becoming parent through parental and marital relationships are more worth striving for (Parry, 2010; 11) (Nauert, 2010).
The illustration below shows the revised pyramid of needs.
Figure 8 Revised pyramid of needs
(Source: Nauert, 210)
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Motivated consumers are ready for actions, which is greatly influenced by consumers’ perception. “How the motivated person acts is influenced by his perception and learning of the situation.” (Pagoso et al., 2008; 78)
Consumers’ perception is based on cognitive complex activities. Selective attention, selective distortion and selective retention are the three main perceptual processes resulting from individual’s perception with exposed stimuli (Kotler & Armstrong, 2008; 135). Brand, value and quality perception have a great impact on consumers’ decision-making process and can be a major driver for continuing or discontinuing the decision-making process. Marketers are focusing on creating value for consumers by increasing added value respectively consumers’ benefit within the scope of brand harmonization (van Gelder, 2005; 197). Consumers’ perception of a brand is highly diverse and is dependent from consumers’ perception process and external influences as personal, social and cultural factors. How a brand is perceived from a consumers’ point of view is influenced by brand’s image, positioning and brand performance. A study conducted by Google in 2011, revealed that 19% of users would have a negative brand perception if a dissatisfaction of performance concerning brands’ website on mobile devices is rated as dissatisfied. Additionally, 61% of users stated that they wouldn’t return to a mobile they had previously trouble with and 75% wouldn’t recommend businesses with a poorly designed mobile site (Pasqua & Elkin, 2013; 111). A further survey conducted by American Interactive Consumer Survey in 2003, underlines the significance of the internet regarding changes in consumers’ brand perception. 45% of all adults with web access have changed their opinion concerning brands resulting from the access to online advertising or online product information (Chain Store Age, 2003; 80).
Within this context consumers’ evoked set has to be mentioned. Consumers’ evoked set is a list of brands that are considered during the decision-making process within the scope of the evaluation of alternatives. Consumers’ evoked set excludes the inept set and inert set, which consists of brand that are not acceptable respectively are not perceived as offering any certain advantage. With increasing experience and category size consumers’ evoked set expands, whereby consumers’ evoked set majorly consists of three till five brands (Schiffmann, 2008; 80). Therefore, learning which is described as changes of consumers’ behaviour caused by information and experiences, impacts the decision-making process by influencing consumers’ perception and the decision-making process. According to Dibb & Simkin, knowledge is the critical aspect and determines the duration and intensity of consumers’ decision process resulting from consumers’ familiarity based on prior experience in purchasing and using the product (Dibb & Simkin, 2013; 137).
2.5 Types of buying behaviour
Buying behaviour is complex and varies among products and services purchased, and consumer’s decision making-process differs concerning the type of buying decision. Lamb et al. emphasise, that routine response behaviour, limited decision making and extensive decision making as types of consumer buying decisions can be differentiated by the involvement, time, cost, information search and number of alternatives.
The graphic below illustrates the three types of buying decision and the characteristics of each contributing factor.
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Figure 9 Continuum of Consumer Buying Decision
(Source: Lamb et al., 2013)
Routine response behaviour refers to products for which only a small number of alternatives are available, cost and involvement are low, consumers invest only little time and the information search takes place only internally based on previous experience, knowledge and learning. Frequently purchased and low costs products or services are covered by the routine response behaviour. Limited decision-making requires a moderate level of time concerning gathering information, the evaluation of alternatives and consumers’ involvement. Lamb et al. describe, that limited decision-making occurs when a consumer has previous product experience but is in general not familiar with current brands which are available on the market. Consumers have to invest a little time in research for finding alternatives in case the favoured product is out of stock, due to the fact that only a limited number of alternatives are in consumers’ evoke set (Lamb et al., 2012; 197). Consumers pass through the extensive decision-making process when buying expensive, infrequently purchased products with which consumers are lacking previous product experience. Hence, information is gathered by internal and external sources and the evaluation of alternatives is detailed and time consuming.
With an increasing complexity and spending, consumers’ are more likely to be involved within the scope of buyer deliberation and buying participants (Talloo, 2007; 161). Besides the previous described approach of continuum consumer buying decision, another approach has to be examined, which lead to the identification of buying behaviour. Henry Assael identified contributing factors and consequently determined four types of buying behaviour. The contributing factors are consumers’ level involvement and differences between brands from consumers’ point of view (Kotler & Armstrong, 2008; 137) (Iman, 2006; 136). Assael’s theoretical framework provides an insight in different types of buying behaviour.
The graphic below illustrates the correlation between consumers’ level of involvement and perceived differences between brands from which the four types of buying behaviour are deduced.
Figure 10 Four types of buying behaviour
illustration not visible in this excerpt
(Source: mba-lectures.com, 2010)
The level of involvement describes, to which extent consumers’ are actively involved in the process of information gathering, product evaluation and the evaluation of alternatives. Dibb and Simkin emphasise, that the level of interest, emotion and activity a consumer is prepared to expend on a particular purchase is described as involvement (Dibb & Simkin, 2013; 506).
2.5.1 Complex buying behaviour
Complex buying behaviour requires high consumers’ involvement and the fact that consumer perceive a significant difference between brands. Kotler and Armstrong explain, that a complex buying behaviour occurs for products or service which are expensive, risky, purchased infrequently and highly self-expressive (Kotler & Armstrong, 2008; 137). Cant et al. add the perspective of buyers required assistance in learning and consequently increasing their knowledge concerning product’s attributes and benefits, due to the infrequently purchase rate of certain products. Motor vehicle, electronics, computer, clothes and furniture are product categories that are likely to cause a complex buying behaviour (Cant et al., 2007; 63). Yeoman describes, that the internet made purchasing more transparent and the consumers’ power increased, consequently services changed due to the fact that consumers are more likely to share information. “The End of Inefficiency is the rapid evolution of intelligent, data-mining systems and algorithms which can make informed, accurate and optimized choices for the consumer” (Yeoman, 2013) Consequently, consumers will be more likely in future to reduce their involvement in complex decision-making processes. “By analysing personal information in ways that no individual could or would want to replicate, services are appearing that can relay advice on the best moment to purchase a deal, the most competitive or value-laden brand (..)”(Yeoman, 2013)
2.5.2 Dissonance-reducing behaviour
In contrast to complex buying behaviour, high involvement and few differences between brands lead to dissonance-reducing buying behaviour. For instance, purchasing a carpet is self-expressive, occurs infrequently, relatively risky and expensive. Moreover, consumers’ might not identify major brand differences. Thus, consumers’ respond in most cases to price advantages and purchase conveniences.
A post-purchase dissonance is likely to occur if consumers experience product related disadvantages and receive information regarding superior or additional benefit from other brands. After-sales service and communication are a suitable tool to reduce post-purchase dissonance and to support the buying decision (Govindarajan, 2007; 91).
2.5.3 Habitual buying behaviour
Habitual buying behaviour is characterized by low consumer involvement and only a few perceived differences in terms of brand from consumers’ point of view. Consumers purchase a product or service habitual, due to consumers’ experience and needs. For instance newspapers, magazines, beverages and petrol are purchased within the scope of habitual buying behaviour. “Buyers are not highly committed to any brands, marketers of low-involvement products with few brand differences often use price and sales promotion to stimulate product trial.” (Kotler & Armstrong, 2008; 138)
Adcock et al. explain, that children influence the purchase decision of sweet brands based on conveyed brand messages from innovative and exciting websites (Adcock et al., 2001; 83). An existing habitual buying behaviour concerning one sweet brand might be replaced by another habitual buying behaviour towards another brand.
2.5.4 Variety-seeking buying behaviour
A low consumer involvement and significant brand differences describe a variety-seeking buying behaviour. Consumers are more likely to switch brands and broaden their brand experiences. During the consumption process the brand is evaluated by consumers. Brand switching is more likely to occur for the purpose of variety seeking instead of consumers’ dissatisfaction. “This type of buying behaviour does not apply to high-value items except where the wealth of the individual is such that this would be a trivial purchase.” (Adcock et al., 2001; 83)
2.6 Types of shopper
The explanation of different types of shopper provides a series of personality mind-sets that are involved along the decision-making process and adds another dimension to the previously defined types of buying behaviour.
The table below concerning key shopper factors shows the combination of possible influences on personality mind-sets and needs concerning a shopping trip.
illustration not visible in this excerpt
Figure 11 Key Shopper Factors
Abbildung in dieser Leseprobe nicht enthalten (Source: Flint et al., 2014)
Stahlberg and Maila describe, the importance to identify different consumer mind sets, which lead to a different type of shopper (Stahlberg & Maila, 2012; 41).
The following eight shopper types are briefly described to provide a further insight into the different shopper types.
1. Keeper: enjoys shopping and responsibility resulting from the importance of shopping goods for the family
2. Seeker: is looking for new ideas, experiences, products and tastes.
3. Banker: budget-oriented shopper seeks discounts and can be retained as customer based on low prices
4. Courier: characterized by small grab and go trips
5. Quartermaster: shopping groceries is seen as a disliked duty
6. Reluctant Shopper: dislike shopping trips and prefers a quick end
7. Bargain Hunter: reducing costs is the primary motivation and only a limited numbers of products are in the evoke set
8. Hungry Shopper: seeking for a specific product in order to satisfy needs immediately e.g. quick meal and cigarettes, if a specific product is not available this type of shopper can turn into a desperate shopper who doesn’t consider shopping at certain shops for the next trip due to the lack of satisfying a need
3 Research questions and hypotheses
Within this chapter the research questions and hypotheses are defined, in order to provide a framework for the relevant analyses regarding the impact of location-based marketing on consumers’ buying behaviour.
As stated within the context of the literature review consumers’ buying behaviour underlies complex processes, such as the decision-making process which is impacted by social, cultural, personal and psychological factors.
Due to the overall objective to determine the impact of location-based marketing on consumers’ buying behaviour, it is relevant to differentiate if information is gathered actively or if information is provided automatically based on consumers’ location. As mentioned previously location-based services inform consumers for instance about special offers or discounts nearby their location by location-based advertising, consequently information is provided and not actively gathered by consumers. “ Shoppers look for information online, in stores or from other sources. They will make purchases online or in brick-and-mortar stores. They will often start in one venue and finish in another. [..] Throughout their journey they expect a seamless experience between online and offline sites. ” (Wilkins, 2013)
Based on this the research questions are defined:
1. What is the key to success to attract new potential customers by using mobile advertising?
2. Do potential customers’ gather actively more information with their mobile devices before purchase compared to customers being addressed by location-based advertising?
Consequently, four hypotheses are defined for examining the impact of consumers’ involvement and the key to success to attract new potential customers by using mobile advertising.
The following hypotheses refer to success factors in order to attract new potential customers by using mobile advertising are examined within the following hypotheses.
H1: Frequent app users and respondent towards mobile advertisement are more lifestyle-orientated.
H2: Frequent users of shopping apps and respondents to mobile advertisement illustrate a higher price sensibility compared to non-frequent users and non-respondents to mobile advertisement.
The aspect of customers’ information gathering activities before purchase compared to customers’ information gathering activities when being addressed by mobile advertising based on their location, is addressed by the following two hypotheses.
H3: Users of shopping apps demonstrate a higher involvement during the purchase process compared to users of shopping apps.
H4: Shopping app users are more likely to gather information and purchase across-channels
4 Methodology and data collection
After the research questions and hypotheses were defined in the previous chapter, the methodological and data collection approach are explained in this chapter.
4.1 Methodological approach
In general research approaches are differentiated between deductive and inductive approaches. The inductive approach describes that prior defining the theoretical framework or theory, data is collected. Whereas the deductive approach defines that the theory and hypotheses are developed followed by the design of a research strategy in order to test the hypotheses (Saunders et al., 2009; 129). “Hypotheses are specific expectations deduced from the framework of a theory […] and consist of a conditional assertion involving the relationship between two or more variables […] and are stated in a form for sutiable testing via empirical research.” (Cargan, 2007; 33). Cargan states, that deductive theories are designed by studying the relevant theoretical background and the development of a deductive approach begins with the re-examination of other studies and relevant theoretical frameworks (Cargan, 2007; 31). The deductive approach is the basis for this master dissertation. Concerning the known three different types of research designs consisting of exploratory, descriptive and causal research, a combination of exploratory and descriptive research design is the most appropriate for the present master dissertation. Causal researches are designed to determine cause and affect relationships and are tested by experiments. Within the scope of descriptive research design characteristics of objects, people and environments are described in order to explain certain situations (Zikmund et al., 2013; 53). Further, descriptive research designs focus on the determination of frequencies or the identification of relationships between different variables (Churchill & Iacobucci, 2005; 74). The purpose of the descriptive design is to identify and measure characteristics, such as consumers’ involvement and the impact of location-based marketing on consumers’ buying behaviour. This master dissertation’s research design describes who, how, where and when concerning the impact of location-based marketing on consumers’ buying behaviour.
The exploratory research design is used to clarify situations and to gain an insight in order to develop new ideas. “As the name implies exploratory research is not intended to provide conclusive evidence from which to determine a particular course of action.” (Zikmund et al., 2013; 52) The three research designs are interrelated at certain stages depending on the research objectives, nevertheless the exploratory research designs is seen by researchers as initial step for the purpose of information research in order to deepen the knowledge concerning certain topics. The exploratory research approach within the scope of this research helped to narrow the information, defining research questions and hypotheses, clarifying concepts and increasing the researcher’s familiarity with the problem (Churchill & Iacobucci, 2005; 76). This research is based on secondary data in form of theoretical frameworks and market data which are complementary to primary data due to a potential lack of accuracy and match with the research objectives, which are implied with the usage of secondary data (Churchill & Iacobucci, 2005; 169). The advantages of the approach of using secondary data are great resulting from the reduction of time and costs, and the availability of secondary data. Primary data is collected by conducting a survey. The quantitative research methodology for this research is applied in order to quantify the data and to apply statistical analysis (Malhotra, 2007; 143).
4.2 Sampling approach and data collection
The examined market for this research is Germany and focuses on consumers’ who have a mobile device, live in Germany and who are in the age range from 18 till 35. The age range results from the high smartphone penetration rate among these consumers’ and their enormous experience regarding downloading apps in developed countries (Cf. Appendix 5 / 6). Further, detailed studies concerning the penetration rate for different age groups, responding rate to location-based advertising or the application rate of location-based services are not available for the examined German market. With a confidence level of 95% and a confidence interval of 5 the required minimum sample size is 384. Accuracy is required in terms of results, consequently a 5% confidence interval, which is actually a 10% range, is defined. This 5% confidence interval has been selected based on Gallup Poll’s expertise which is a leading market research company in the US. Furthermore, a confidence level of 95% has been selected due to the fact that it is the most common one used in researches (Yang & Miller, 2008; 228). A detailed determination of the researched population such as number of smartphone users per age group or smartphone penetration per age group for Germany is not relevant to consider. “If one’s population is 10.000 or larger, then the population size does not affect how big a sample is required.” (Yang & Miller, 2008; 228) Thus, the confidence level of 95% and a confidence interval of 5 determine the sample size of 384.
In order to ensure data validity and reliability a purposive sampling approach which is a nonprobability sampling method is used. “The advantage of purposive sampling is that the researcher can use his or her research skill and prior knowledge to choose respondents.” (Bailey, 1994; 96)
The required data is collected by conducting face-to-face interviews and the distribution of an online survey via Xing.com, LinkedIn and Facebook. 131 online surveys were filled out and 312 face to face interviews were conducted (total 443 > prior defined minimum sample size of 384). The online survey (Cf. Appendix 6 / 7) was designed with q-set.nl and is distributed in English and German language along the online channels which underlies the assumption that some respondents might feel more comfortable with English. This may result from immigration. Kotler and Armstrong state, that languages are the most obvious obstacle for marketers besides cultural differences from country to country which might lead to occurring problems (Kotler & Armstrong, 2008; 112). The data set is analysed with SPSS 21. The main advantage of online surveys is that these are inexpensive, the short response time and saving of time concerning data collection and the input of data (Hollensen, 2007; 173). The low completion rate during the testing period via LinkedIn and e-mail showed that the lack of direct interaction between interviewer and respondent is a major disadvantage. The target group for the selected online channels is broad concerning the target group requirements, concerning the age range and country of residence.
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