Consumer Identity Inventory: A New Tool For Segmenting Online Consumers?

Abstract

Individuals’ sense of who they are as consumers influence their consumption behaviors. In this context, "consumer identity" may be used as an alternative segmentation criterion that may help to explain the variation in consumption patterns. This study aims to offer a Consumer Identity Inventory (CSI) to measure consumption-specific identities and investigate the efficiency of an approach of using those identities to segment the online buyers. In this context, we conducted two studies in Turkey. In the first study, we explored 60 consumer identities through Twenty-Statement-Test (TST) that is conducted on 186 participants. Then, CSI was formed based on the findings of TST. In the second study, we examined the relationships between consumer identities and online buying tendency using the data collected from 343 participants through a survey. Results revealed 19 consumer identities that promote online buying and 19 identities that discourage online buying. Findings are discussed in detail, implications for future research and suggestions for online retailers were provided.

Keywords: Consumer identity inventoryonline buyingsegmentation

Introduction

Technology era has made significant changes in business models and today e-commerce is an essential part of companies. E-commerce provides a new shopping platform for consumers where consumers search, find and buy products online (Keeney, 1999), and the internet has become to be a global commerce tool for companies. Online shopping trend is growing rapidly among buyers all over the world, and it is also a constantly increasing shopping channel in Turkey. E-commerce market size report of TÜBİSAD revealed that 76% of the UK population is online shopping user, Germany, and Japan following with 72% and 68%, respectively. However, Turkish Informatics Industry Association (2016) the average rate of online shoppers is a bit low in developing countries; Turkey has a place at similar levels to developing countries such as BRICs. According to the latest statistics by Turkish Statistical Institute (2017) slightly one of four Turkish consumers used online shopping in 2017 Despite the momentum captured in the online retailing in last years, the share of online’s in total retail sales was 3.5% in 2016 while the world average of 8.5%, signaling that there is a significant room for growth (Turkish Industry and Business Association, 2017). Indeed, Turkey has a substantial potential for e-commerce with 46 million internet users and 58% internet penetration (Turkish Industry and Business Association, 2017). However, to benefit this potential, it is essential to understand the expectations, motivations, and concerns that promote or hinder Turkish consumers’ online shopping behavior. As reported by Aljukhadar and Senecal (2011), consumer-revealed segmentation can be used to identify naturally occurring customer groups which will help companies to gain a strategic advantage over their competitors by helping them to identify the unique attitudes, motives, characteristics, and needs of the divergent segments and thus to translate strategic opportunities into an actionable plan.

It is well documented that online shopping offers a variety of benefits to consumers over traditional shopping channels. Lower prices, product comparison opportunity, good product descriptions, time saving and easy transaction systems (Limayem, Khalifa, & Frini, 2000) convenience, pleasure and website design and presentation of information influence consumers to buy online (Clemes, Gan, & Zhang, 2014; Gupta & Kim, 2010; Mosteller, Donthu, & Eroglu, 2014) are some factors that promote online buying. However, country-based studies show that perceived benefits may vary among different countries (Lim, Osman, Salahuddin, Romle, & Abdullah, 2016). For example, price and promotion is the most important motivator for Greek online shoppers (Papppas, Kourouthanassis, Giannakos, & Lekakos, 2017), usefulness is a motivation tool for Spanish consumers (Hernandez, Jimenez, & Martin, 2011), Korean consumers prefer a nice website design and pictorial information, while Turkish consumers requires security and detailed information (Hwang, Jung, & Salvendy, 2006). These studies reveal that consumers from different countries may change in preferences, expectations, and consequently response to online buying.

To date, various criteria are offered for segmenting online buyers including demographics, psychologic and behavioral differences, and other personal variables. For example, it is found that demographics influence consumers' information search and online buying behavior (Ahuja, Gupta, & Raman, 2003). Consistently, Kau, Tang, and Ghose, (2003) found that it is possible to get a distinction between online shoppers' profile from their demographics and actual shopping behavior. Using a behavioral approach Barnes, Bauer, Neumann, and Huber (2007) segmented online consumers in Germany, USA, and France based on their attitude towards online shopping, trust, perceived risk, shopping pleasure, purchasing intention. They explored three groups of online buyers including risk-averse doubters, open-minded online shoppers, and reserved information-seekers. Liu, Li, Peng, Lv, and Zhang (2015) segmented online consumers into six types based on their buying behavior indicators, namely economic buyers, high loyalty buyers, active-star buyers, direct buyers, risk-averse buyers, and credibility first buyers. Hill, Beatty, and Walsh (2013) identified adolescent internet users and shoppers as internet conquerors, virtual pragmatists, and recreational shoppers based on their motivations. In the study of Kemeny, Simon, Nagy, and Szucs (2016), Hungarian online bookstore consumers were segmented based on their electronic service quality perception. Four groups of consumers appeared including Website’s soft skills underrated, happy, technology underrated and unhappy consumers who have a different level of satisfaction and word of mouth intention. Dirsehan and Celik (2011) aimed to descript new customer segments with online consumers' brand and social experiences; they found seven online consumer groups; individual hedonists, highly socials, holistic consumers, action-oriented consumers, knowledge seekers, sense-directed and social utilitarian consumers. Mathew (2016) segmented Indian online consumer behavior based on e-usage attitude; it is found that a higher level of internet usage increases trust and usefulness of online buying. Lissitsa and Kol (2016) utilized Generational Cohort Theory as a market segmentation tool; interestingly Generation X purchase electrical products, furniture and holiday online at a higher rate when compared with Generation Y.

Reimer, Rutz, and Pauwels (2014) conclude that the effective marketing approach is based on consumer differentiation by segmentation; however, standard segmentation tools may fail to identify segments that are homogeneous enough. For this reasons, in this study, we offer "consumer identity" as an alternative segmentation criterion that may help to explain the similarities in online consumption patterns and responses to pros and cons of online shopping. Although prior research revealed that identity and consumption behavior intimately connected (Hansen, Sorensen, & Eriksen, 2018; Weiss & Johar, 2013), there has been no study that explored the relationship between the consumer identity and online shopping behavior, to the best of our knowledge. Aiming to fill this gap to some extent, we investigate the relationship between consumer identities and online shopping attitude and intention. The research results may provide useful insight for marketing managers that perform in Turkish e-market.

Literature Review and Theoretical Framework

Consumer identity as a segmentation tool

Hogg and Abrams (1988, p.2) defined identity as “people’s concepts of who they are, of what sort of people they are, and how they are related to others." Our belongings determine our identity formation and reflect our identity (body, personal space, foods, homeland, spouse, children, friends, objects, entertainment, pets, and memories) (Belk, 1998). Typically, identity let individuals arrange their social categories and individual characteristics in common ground, individuals use identity to define their personal traits, and certain categories can be accepted as individuals' identity (Fearon, 1999, p.2).

A variety of labels can be associated with the self, chronically or in specific situations (Reed II, Forehand, Puntoni & Warlop., 2012). Hall (1996) examined identity into three groups; personal, social and postmodern. Personal identity explains individualistic differences and social identity explains an individual's connection to the society (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987). According to Hall (1996,), postmodern identities are active, adaptable, social and the subject is not only belonging to one stable and ‘objective' identity (e.g., mother, son). Identities are fragmented by class, gender, ethnicity, race and many other groups. This fragmentation is changing the subject's personal identity forming because people are reflexive and they generate their multiple identities by making self-categorization and identification in terms of membership in particular groups or roles to behave appropriately (Burke & Reitzes, 1991; Stets & Burke, 2000; Wilska, 2002). Consumption is also a membership to brands, stores or other shopping-related issues. In such research, consumption is an important component of forming and exhibiting identity especially in today's modern society (Giddens, 1991).

On the other hand, people may adopt a special set of self-labels for consumption contexts based on their preferences, interests, wishes, activities, habits and some psychological attributes (Gatersleben, Murtagh, Cherry, & Watkinset, 2017). Self-labels that help to make sense of who we are when it comes to our consumer behaviors may be termed as "consumer identities" (e.g., trend follower, recycler). Reed II et al. define consumer identity as “any category label to which consumer self-associates that is amenable to a clear picture of what the person in the category looks like, thinks, feels and does” (2012, p.310). In their study, Gatersleben, Murtagh, Cherry, & Watkins, (2017) revealed 25 distinct consumer identities that respondents used to describe themselves consumers (e.g., frugal, bargain hunter, impulsive, planner). Researchers also found that moral, green and environmental identities were important predictors of a range of pro-environmental consumption. These findings are consistent with the argument that once an identification is formed, consumers initiate a process to become that kind of person, look for internal and external feedback to reinforce their identity (Reed II, Forehand, Puntoni, & Warlop, 2012). In other words, when individuals know who they are as consumers “who they are” directs their future choices in an identity-congruent route (Oyserman, 2009).

Marketing practitioners benefit from identity as a reference point while positioning their brands through communication campaigns which often signal the match between relevant brands and identities of the target consumer group. We suggest that "consumer identity" may also be a convenient tool to segment the market. This is because when consumers view themselves in a specific category ( e.g., green consumer) a wide range of "identity-driven effects" emerge s such as (1) increased attention to identity-related stimuli (2) a preference for identity-linked brands (3) more positive reactions to advertisements featuring spokespeople who possess the desired identity (4) the selection of media catering to the identity, (5) the adoption of behaviours linked to an identity, (6) and biased attention toward identity-consistent memories (Reed II et al , 2012). It appears that salient identities serve as organizing schemas for integrating new information and experience into the self-concept and consequently influence perception, judgment, and self-regulation (Shavitt, Torelli, & Wong, 2009). More specifically it is reasonable to indicate that psychologically salient consumer identities may efficiently be used to create segments, not with only similar buying motivations but also identical consumption habits, activates, orientation, styles, preferences, wishes and psychological attributes which are closely related with consumption processes.

Research Method

For the aim of the research two studies were conducted on separate samples. The first study aimed to distinguish consumer identities that are salient to Turkish consumers. For the second study, those distinguished identities were turned in to a Likert scale format to form a "Consumer Identity Inventory (CII)". At the second study, a survey was conducted on a small but heterogeneous sample to measure consumer identities and online shopping orientations. The second study allowed to evaluate the link between identities and online buying.

Study 1: The Twenty Statements Test

As stated above the first study aimed to explore a set of identities that are used by Turkish consumers to describe themselves. The Twenty Statements Test (TST) which was first introduced by Kuhn and McPartland (1954) as an instrument to measure self-concept was employed for this aim. Gatersleben et al., (2017) proved that The TST was a useful tool to explore how people describe themselves as consumers.

Table 1 -
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Instrument and Sample

Following a similar procedure with Gatersleben et al., (2017) a single-page form was designed with a description part, and twenty numbered blanks. The description indicated that “consumers are persons who purchase, use and dispose of the goods and services for personal benefits. Please complete as many statements about yourself as possible in response to the question: ‘When it comes to my consumer behavior I am ….'. Please answer as if you are giving the answers to yourself and write your answers in the order they occur to you. Don't worry about logic or importance. Go along fairly fast." The form was distributed to a sample that was chosen through a convenience sampling technique among the consumers living in İstanbul and Kocaeli, Turkey. 186 valid responses were obtained after the elimination of the forms with a single-statement response. The sample consisted of 108 women (58%) and 78 men (42%) with the mean age of 31,25 years (SD =11,54).

The Twenty Statements Test Results

A coding scheme that is used by Dirsehan (1989) and Gatersleben et al., (2017) was employed. In this study, we focus on only attributive identities including subcategories of preferences, interests, wishes, aspiration, activities, habits and qualified psychological attributes for coding because they are relevant for a consumption context. Comparison between codding by two researchers yielded a 91% agreement. As a result, 60 consumer identities emerged. Some of the identities referred to preferences, interests, wishes, aspiration that guide consumer choosing products and retailers among alternatives (e.g., quality oriented, esthetic oriented, health-oriented) while the most of the identities referred to a general consumption style (e.g., researcher, budget planner, indecisive, variety seeker). Besides, some consumer identities referred the product usage habits (e.g., attentive, conservative, fixer). Finally, a group of identities referred to the activities, and habits regarding the disposal of the products (e.g., re-user, second-hand seller, keeper, recycler). A full list of 60 consumer identities is presented in Table 1 in a rank from most to least frequently stated.

Study 2: Consumer Identity Inventory Survey

Instrument and Sample

Based on the results of TST a Consumer Identity Inventory (CII) was developed with 60 labels that Turkish consumers use to describe themselves. Descriptions, which are displayed in Table 1 for each identity, were used to form Likert scale items (e.g., I am an advice seeker as a consumer who needs to hear advice from my friends and family) with 5 point response options (1=Strongly disagree, 5= Strongly agree). The questionnaire was pretested with a small sample to check for ease of responding, clarity of instructions and questions. The final questionnaire also included 15 items measuring respondents' attitude toward online shopping and online shopping intention. These items were adapted from Chen, Gillenson, and Sherrell (2002), Ko, Kim, and Lee (2009), Vijayasarathy (2004) and Yang (2012).

The questionnaire was distributed to a total of 343 participants which were selected using a convenience sampling method. Women comprised 40 % of the sample relative to 60% of men. The respondents were aged 18 to 69 years, and the mean age was 28 (SD=10,95). Only 30% of them were married while the rest were currently single. Slightly half of the respondents had an annual, monthly income in the range of 2.000-5.000 ₺while 13% reported an income less than 2.000₺. The data show that 31% of the respondents had a monthly income between 5.000-10.000₺ and less than one in ten respondents had 10.000₺ and more income. Descriptive statistics also revealed that 5% of the respondents completed secondary school, while more than a half (56%) had a high school education and finally 41% had graduate and postgraduate education.

Survey Results

Initially, 15 items measuring online buying attitude and intention was subjected to exploratory factor analysis (EFA) using principal components analysis and oblique rotation. EFA revealed three factors with eigenvalues greater than one which explained 74% of the variance in total. Two attitude items which are related to the risk of online buying were loaded to a separate factor that is interpreted as “perceived risk”. All factor loadings were higher than .700. Moreover, alpha coefficients for these scales ranged from .84 to .95 providing support for reliability (Nunnaly, 1978). Then, for subsequent analyses, composite scores equivalent to the arithmetic means of the item scores were calculated for each online buying variable. Because consumer identity inventory is not interpreted as a reflective scale, it was not subjected to the traditional validation process. Mean scores and standard deviations for each consumer identity are presented in Table 01 .

The relationship between identities and online buying tendency was evaluated through Pearson correlation analysis and results were reported in Table 2 . Although correlation coefficients are fairly low it is safe to state that there are three groups of consumer identities based on their relation to online buying tendency: (1) Identities that are not related with online buying, (2) Identities that are positively related with online buying, termed as “identities that are salient for online buyers” and (3) Identities that are negatively related with online buying, termed as “identities that are salient for online buying avoiders”.

Identities that are not related to online buying: About one-third of the identities were not significantly related to online buying variables. It is somehow reasonable since Consumer 01Identity Inventory (CII) do not focus on a specific consumption context (e.g., online buying) but general consumption patterns. However, some interesting findings were that salience of the "deal hunter," and "thrifty" identities do not have an encouraging effect on Turkish consumers buy online. Although lower prices are indicated one of the most important benefits of online buying (Limayem et al., 2000) it may not be a significant motivating factor for “deal hunters” and “thrifty” consumers in Turkey.

Identities that are salient for online buyers: The results show that the label of “online buyer” that consumers use to describe themselves is closely related with their online buying attitudes (r=.497, p<.01) and intentions (r=.686, p<.01), supporting the argument of Reed II et al., (2012) that once the consumer has begun to use a category label to describe his/her self he or she just become that kind of consumer. In addition to “online buyer” identity, there are 13 other identities that are likely to promote consumers’ future online shopping. Results showed that consumers who describe them self as a trend follower, technology lover and/or brand loyal have more favorable believes regarding the benefits of online buying. It appears that the internet provides a more convenient, time-saving way for these consumers to reach a very large product selection of numerous brands and their latest models.

Table 2 -
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**Correlation is significant at the 0.01 level (2-tailed), * Correlation is significant at the 0.05 level (2-tailed).

a Consumer identities which have no relationship with any of online buying variables were not included.

Besides "researchers", "quality oriented" and "rational" consumers are more likely to buy online, probably because it is much faster and easier to get more and detailed information about the products, compare the alternatives and chose a product with a high quality-price ratio. This interpretation is consistent with the previous finding that the main motivation for online shopping is the ability to easily search for information (Kumar & Thakur, 2016; Punjand & Moore, 2009). Correlation analysis also revealed that internet provides a so convenient and maybe socially acceptable medium for selling and buying second-hand products that “second-hand sellers" and "second-hand buyers" are more likely to buy online. Moreover, “advisors”, who like to inform other people about their experiences with products, have favorable attitudes and greater intention to buy online. This is probably because online shopping platforms provide an opportunity of informing numerous people.

Interestingly, another consumer identity that supports online buying is "The queen/king" which identifies the consumers who expect a salesperson to be highly subservient and willing to answer the question and solve the problems. It appears that service, support, and information provided by the online vendors satisfy consumers need for care, which they expect from salespersons in conventional stores. Interestingly, "keepers" and "stockers" who just prefer to keep products for eventual future needs are more prone to buy online. Another interesting finding is that "suspicious" consumers have positive evaluations regarding the benefits of online buying probably because they found internet as an open, self-service retailer with no aggressive persuasion efforts. Finally, "crowd avoiders", who avoid shopping traffics of malls are more likely to favor online buying. It is reasonable since online stores which are accessible 24/7 and 365 days with little or no cost permit a calm and peaceful shopping experience.

Identities that are salient for online buying avoiders: There are some consumers who adopt “internet avoider” label to describe their consumer behavior because they certainly avoid shopping online. As expected, a strong inverse relation was found between the salience of this identity and online buying attitude (r=-.563, p<.01) and intention (r=-.711, p<.01). Results also showed that “waste avoiders”, “re-users”, “donors”, “greens”, and “simple” consumers are less likely to buy online. It is safe to state that these identities may take root in an eligible concern for environmental degradation caused by over-consumption. Hence, consumers holding this group of identities are likely to reduce buying new products, even from online stores, and prefer to extend the life of existing products. It is also evident that "health-conscious" consumers avoid online buying probably because they prefer local stores which supply very fresh and organic foods. Furthermore, "shy" consumers who are not good at claiming their consumer rights were found to avoid online shopping. This may be explained by a foresight regarding eventual arousal of necessity making a return request for an incorrect, failed or shipping damaged product which is more issue at online buying. Indeed, concern regarding online merchant’s competence to fill the internet orders is indicated as one of the most significant barriers to online shopping (Jarvenpaa, Tractinsky, & Vitale, 2000). It appears that those concerns are discouraging especially for “shy” consumers who do not feel ready to fight for their rights.

On the other hand, “bazaar lovers” and “non-loyals” were found to have another sense of insecurity regarding online buying. They are relatively more prone to feel the risk of online payment, and that's why they are less likely to buy online. Most likely, because they are not loyal to any specific brands they may be satisfied by any available products that can be interacted physically, so they don’t take the risk of online payment. On the other hand, “bazaar lovers” may be enjoying physical shopping experiences. Finally, analysis results revealed that there is a group of identities which do not directly hinders the positive attitudes or intentions of Turkish consumers for online buying but intensifies the perceived risk. It is well documented that consumers see significant risks and uncertainty in non-store purchase decisions (e.g., Friedman, Kahn & Howe, 2000). More specifically, consumers who describe themselves as "energy/water savers", "frugal" and "forethoughtful” experience a higher level of concern regarding privacy and insecurity of financial transactions. It is not surprising since those identities may share a common motivation to save money. Thus, consumers adopted those labels are likely to be more sensitive to eventual financial loss.

Conclusion and Discussions

Alike with previous research, this paper offers consumer identities as a segmentation criterion based on the assumption that consumer identity is a mediator between consumption motivation and behavior (Hansen et al., 2018, p.40). Accordingly, consumers’ lifestyle, attitude, values, etc. motivate them to buy while consumer identity influences their final consumption behavior. So we suggest that consumers may be segmented as to self-labels they adopted for consumption contexts. Within this scope, we offer a Consumer Identity Inventory comprising of 60 identities referring to preferences, interests, wishes, aspiration, activities, habits, psychological attributes that guide consumer behavior. Then, we specify the identities that are directly and indirectly related to online shopping. Findings revealed that some identities are useful to predict who is more and less likely to buy online. For example, trend followers, researchers, technology lovers, advisors, second-hand buyer-sellers, crowd-avoiders are more prone to buy online due to some distinct benefits offered by online vendors. These results provide meaningful insights for managers since they may focus on web designs that encourage feedbacks from "advisors", update the product-mix often to attract trend followers, or provide intensive and detailed information for "researchers" while they focus on presenting some quality ques for "cognitive closers". On the other side, an online vendor may position itself as pro-environmental or highlight environmental benefits of online purchasing to attract the “waste avoiders”, “re-users”, “donors”, “greens” and “simple” consumers who avoid online buying. Besides, “budget planners”, “energy/water savers” and “frugal” consumers should be communicated through both economic advantages and high-security system while addressing warranties and after-sale services for “forethoughtful” consumers.

In sum, the results provide a foundation for future research on Consumer Identity Inventory. Besides, it offers an alternative explanation for online buying behaviors through identity which a stable variable. The results of the presents study suggest that consumer identities may be used as an effective segmentation tool especially when they are combined with some other conventional segmentation variables such as demographics.

It is essential to note that this study has some limitations. First of all, our sample is relatively small and drawn from İstanbul and Kocaeli, Turkey by convenience sampling method. Therefore, the generalization of the finding should be approached with caution. Besides, this is the first study that explores and apply the Consumer Identity Inventory (CII) in a specific consumption context, namely online buying. Future research should continue to test and to refine the scale. Future studies could also take a broader view of the relationship between consumer identities and behaviors.

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Publication Date

18 December 2019

eBook ISBN

978-1-80296-053-2

Publisher

Future Academy

Volume

54

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-

Edition Number

1st Edition

Pages

1-884

Subjects

Business, Innovation, Strategic management, Leadership, Technology, Sustainability

Cite this article as:

Gündüz, S., Kabadayi, E. T., & Dursun*, İ. (2019). Consumer Identity Inventory: A New Tool For Segmenting Online Consumers?. In M. Özşahin, & T. Hıdırlar (Eds.), New Challenges in Leadership and Technology Management, vol 54. European Proceedings of Social and Behavioural Sciences (pp. 547-559). Future Academy. https://doi.org/10.15405/epsbs.2019.01.02.46