Behavioral Issues in B2C E-commerce

Online Consumer Behavioral Issues

Articles related to online consumer behavioral issues in B2C e-commerce platforms attempt to determine various critical factors influencing consumers’ attitudes and behavioral intentions toward online shopping. Factors identified under this category includes consumers’ Internet usage and previous online shopping experiences, shopping motivation, personal traits, risk and benefit perceptions, trust perception, subjective norms and perceived behavioral control. The following paragraphs discuss each factor respectively.

Two types of online consumer shopping motivation that are utilitarian and hedonic have been examined quite extensively in the relevant literature [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]. While utilitarian shopping motivation is defined as goal oriented and mission critical, hedonic motivation refers to consumers’ shopping behaviors that focus on enjoyment, satisfaction, happiness and sensuality [7]. Utilitarian and hedonic shopping motivation has been found to be positively associated with customer satisfaction and purchase intention [11, 13, 14]. These two motivational factors also affect consumers’ intention to spread positive word-of-mouth information on the web about online retailers [8]. Several studies assessed the influence of emotional factors such as satisfaction [9, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27], enjoyment [9, 28, 29, 12] and loyalty [25, 26, 30, 31] on consumers’ online shopping behavior. Results of the studies showed that consumer satisfaction with the online retailer’s website is positively related to consumer’s loyalty to it [9, 16, 17, 19] and loyalty has been found to increase the actual website buying frequency [30]. However, shopping enjoyment was not found to influence either online store loyalty [9] or online shopping continuance [12, 29].

In the literature, several articles assessed the influence of Internet usage [32, 33, 34] and previous online shopping experience [29, 35, 36, 37, 38, 39] on online consumer shopping behavior. Findings of the studies showed that the amount of consumers’ Internet surfing hours is positively associated with consumers’ online shopping activity [33, 40] and consumers with high Internet experience are more likely to prefer online shopping channels over offline channels [34]. It was also found that consumers who have previous online shopping experience would perceive less risk than those who have never shopped online before [38]. In addition, higher prior online shopping experience leads to higher online purchase intention [35, 36, 37].

The relationship between online shopping behavior and personal traits such as innovativeness, active involvement, agreeableness, conservation, self-enhancement, self-confidence, openness to experience, individualism, collectivism and risk aversion was assessed by several studies [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]. Active involvement, agreeableness and openness to experience were found to have a significant influence on consumers’ willingness to shop online [42]. Innovativeness in new technology was also found to affect attitude and intention toward online shopping positively [40, 44, 46]. Consumers exhibiting higher levels of horizontal individualism and vertical collectivism are more likely to exhibit higher level of perceptions about the integrity and responsibility of the retailer. Consumers’ perception level, in turn, plays an important role in building loyalty toward online retailer’s services [47]. Zhou et al. [48] found that individualism positively affects not only consumers’ initial trust in an online seller but also their online shopping intention. Furthermore, Yoon [45] showed that the higher the degree of uncertainty avoidance, the lower the effects of trust and perceived usefulness on intention to shop over the Internet.

Consumers’ risk and benefit perceptions were examined in a number of studies by taking their online shopping behavior into consideration. Privacy risk, security risk, financial risk, product delivery risk, product performance risk, psychological risk, social risk and refund risk are among the risk factors whose influence on online shopping behavior were researched quite extensively in the literature [14, 22, 28, 30, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]. Wang et al. [30] and Lee et al. [70] showed that there is a negative relationship between consumers’ perceived risk and their attitude and loyalty toward retailers’ online store. Hong and Cha [51] found that consumers’ perceived financial, performance, psychological and social risks are negatively related to online shopping intention. Furthermore, Huang et al. [67] showed that consumers with previous online shopping experience perceive less risk toward online shopping than consumers who have never shopped online before. On the other hand, researchers analyzed perceived usefulness, perceived ease of use, online product quality, money-saving, time-saving and effort-saving capabilities of online stores as perceived benefit factors [28, 44, 45, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90]. Some of the findings are as follows. Perceived ease of online shopping use is positively related to perceived usefulness of online shopping [73, 78, 80]. Perceived usefulness, in turn, has a positive impact on consumers’ intention to use online stores [44, 45, 83, 91]. It was also found that product quality and time and effort saving features of online shopping significantly influences consumers’ online shopping intention [28].

Researchers assessed the relationship between consumers’ perceived trust and their online shopping behavior and their study results showed that consumers’ trust in online shopping environment originates from various sources. Transaction security and privacy [23, 92, 93, 94, 95, 96, 97], situational abnormalities [98], information and service quality [26, 91, 99] provided by the online retailer significantly influences consumers’ trust level. It was also found that there is a positive relationship between reputation of the company and consumers’ initial trust in online retailer [89]. Consumers’ trust level, in turn, was found to play an important role in influencing online shopping rate. It was found that trust in online retailers positively and significantly influences consumers’ attitudes and intentions toward shopping in online stores [35, 85, 86, 93, 100, 101, 102, 103, 104]. Furthermore, Kim and Jones [105] found that there is a positive relationship between consumers’ offline brand trust and their intention to shop online. E-trust also leads to positive online word-of-mouth advertising; that is, satisfied consumers tell other online consumers how much they liked particular retailer’s products and services [21].

Several studies assessed the influence of subjective norms [46, 54, 86, 106, 107, 108, 109] and perceived behavioral control [46, 54, 107, 109, 110] on consumers’ willingness to shop online. Subjective norm is defined as consumers’ perceptions about online shopping which is mainly influenced by the judgment of parents, friends, spouse, news and media. Subjective norm comes out from two underlying factors that are the normative beliefs the consumer relates with significant referents and the motivation to act according to these referents’ thoughts. Findings of the studies showed that there is a positive and significant relationship between subjective norms and online consumer shopping intention [46, 54, 108]. On the other hand, perceived behavioral control refers to individual’s perceptions of their ability to perform a particular behavior. Studies conducted in Thailand by Laohapensang [107] and in Sweden by Hansen [109] showed that perceived behavioral control on Internet shopping positively influences consumers’ online shopping intention. However, studies conducted in Spain did not find any significant relationship between these factors [46, 54]. These contradictory results might be due to cultural factors. A few studies showed that factors influencing consumers’ intention to shop online varies depending on the nationality of the consumer [130, 132].

Online Consumer Segmentation

Studies classified under this category attempt to segment online consumers based on their demographic, psychographic and behavioral characteristics in order to help online retailers to tailor their products and services according to each segments needs and requirements. The goal of these studies is to show that online consumers are not composed of a single market; instead they are composed of heterogonous groups whose members have different needs and expectations and respond differently to the marketing efforts.

Segmenting and assessing the behavior of online consumers according to their demographic characteristics is one the most commonly followed strategies in the literature. Age, gender, marital status, income and occupation are some of the characteristics upon which grouping is carried out. The influence of consumers’ age [33, 54, 84, 108, 111, 112, 113, 114, 115, 116, 117], gender [11, 13, 22, 23, 33, 54, 84, 96, 108, 111, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,126], marital status [33, 84, 108], income [84, 108, 112, 115, 117, 127], education [54, 84, 108, 112], occupation [54, 108, 115] and culture [26, 45, 128, 129, 130, 131, 132, 133] on online shopping behavior have been examined by many studies. Some findings from the selected articles are as follows. Gong et al. [84], Clemes et al. [108] and Bhatnagar [115] found that the younger the consumers are, the more likely that they will shop online. Individual’s gender also was found to influence online shopping intention significantly [33, 108, 122]. When it comes to marital status, while the study conducted in China by Clemes et al. [108] indicated that single consumers are more likely to shop online, the study conducted in Israel by Liebermann and Stashevsky [33] found no significant relationship between marital status and online shopping rate. These contradictory results show that caution should be exercised while interpreting research findings to different cultural contexts. Study findings of Gong et al. [84] and Bhatnagar [115] showed that the frequency of online shopping is positively related to the income level of the consumer. It was also found that there is a positive relationship between consumer’s education level and online shopping adoption [54, 84, 108]. While Clemes et al. [108] showed that occupation has a positive impact on online shopping adoption, Crespo and Bosque [54] did not find any significant relationship between them. Several other studies found that factors influencing consumers’ intention to shop online vary depending on the nationality of the consumer [130, 132, 133].

Segmentation according to psychographic and behavioral characteristics considers factors such as online consumers’ lifestyle, attitudes, expectations, shopping activities, shopping motivation and orientation. By using e-store attribute importance and online shopping motivation measures, Ganesh et al. [134] found six and seven different online consumer segments respectively. In their study Pradas et al. [135] classified non-shoppers based on the barriers which discourage them to shop online and the drivers which might encourage them to make online purchases. The results of the study gave four different non-shopper segments based on the barriers for online shopping and six different segments based on the drivers to start purchasing on the Internet. By using factors such as web-usage-related lifestyle, themes of Internet usage, demographics and Internet attitude, Brengman et al. [136] determined four online shopper segments (tentative shoppers, suspicious learners, shopping lovers, and business users) and four non-shopper segments (fearful browsers, positive technology muddlers, negative technology muddlers, and adventurous browsers). In their study Liu et al. [137] determined six different online consumer typologies by using real online retail transaction data. These segments are economical purchasers, active-star purchasers, direct purchasers, high-loyalty purchasers, risk-averse purchasers and credibility-first purchasers. Later, they assessed each online consumer group’s sensitivity to three different promotion strategies, which are discount, advertising and word-of-mouth. Results of the study showed that each consumer group responds differently to three different promotion strategies. Other studies determined different online consumer segments based on consumer characteristics [47], shopping motivation [138], shopping orientation [139], consumers’ underlying cognitive style and involvement [140], Internet usage pattern [141], computer expertise and preference structure (i.e., e-store attributes and features) [142] and decision making style [143]. Results of these studies showed that each of the determined consumer groups have different expectations, attitudes and behavioral intentions toward online shopping.

Online Store Features

Studies classified under this category attempt to assess the relationship between online store features (i.e., design, functionality and content) and online consumer shopping behavior.

Studies that focus on online store design factors evaluate online stores’ general design and visual aspects [21, 77, 99, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154], ambience and atmosphere [155, 156, 157] and customer interface features [17, 153,158]. Liao et al. [77] showed that the appearance of an online store positively affects the consumers’ perceptions about online stores' usefulness. It was found that the better consumers perceive online store design to be, the more they get enjoyment and satisfaction [21, 147, 150]. Furthermore, Mummalaneni [155] showed that online store ambient factors positively and significantly influence consumers’ pleasure and arousal levels. Background music tempo within online stores was also found to influence arousal level of consumers positively [156].

Studies that focus on online store functionality evaluate online stores from the perspective of convenience [17, 21, 108, 144, 150, 154, 159, 160], customization [17, 161, 162, 163, 164], technical adequacy [77, 144, 165], usability [166, 167, 168], interactivity [12, 17, 69, 169, 170], fulfillment [87, 171], efficiency [171], complexity [172], navigation [147] and transaction speed [150, 160] and education and entertainment-focused in-store events [173]. It was found that when consumers find the online transaction completion process as inconvenient, they are more likely to abandon the online shopping cart [160]. Online stores that exhibit a high degree of convenience in terms of transaction and search processing positively influence consumers’ online shopping intention and loyalty [17, 159]. Customization was found to positively influence online consumers’ satisfaction, loyalty and behavioral intentions toward online shopping [17, 161]. Customization also makes consumers’ positive emotions stronger in retailers’ online stores [164]. Websites with a high degree of interactivity not only positively influence consumers’ satisfaction and loyalty toward online retailers [17], but also lead to forming initial trust in online retailers [69]. No significant relationship was found between rapid response time in online stores and online consumer satisfaction level [150]. Duration of waiting time to finalize a transaction in online stores was not found to influence the rate of consumers shopping cart abandonment [160].

Studies that focus on online store content assess online stores in terms of general content quality [25, 26, 77, 99, 102, 150, 170, 174, 175, 176, 177, 178, 179, 180], content quantity [178, 181, 182, 183, 184], content presentation [175, 184, 185], informativeness [21, 144, 186, 187] and product variety [108, 150]. The content quality of an online store positively influences consumer’s perceptions about its usefulness [77]. Higher levels of information quality were found to increase consumers’ satisfaction levels and loyalty intentions toward online retailers [150, 174]. It was also found that the higher perceived information quality is, the more likely consumers will choose that online store to shop among competing websites [175]. The degree of perceived information overload increases with the amount of information presented to consumers within online store [181]. An increase in information load leads to a reduction in the consumers’ product consideration set sizes, which are the products consumers seriously consider for purchasing [183]. It was also found that product variety within online stores positively influences consumers’ satisfaction levels and their online shopping adoption [108, 150]. However, information presentation quality was not found to influence consumers’ likelihood to choose a particular online store among competing alternatives [175].

Online Store Credibility and Reputation

Studies classified under this category assess the influence of perceived online store credibility and online seller reputation on consumers’ attitudes and behavioral intentions toward online shopping. Credibility of the online stores was assessed from various aspects such as existence of sound privacy policies [95, 188, 189, 190,191, 192, 193], effective security measures [94, 95, 97, 191,192, 194,195], reasonable delivery services [196] and fair return policies [94, 195, 196, 197]. A number of studies investigated the relationship between online consumers’ attitudes toward making purchases over Internet and the reputation of an online retailer [89, 99, 190, 198, 199, 200, 201, 202].

If consumers do not perceive online stores credibly due to privacy and security issues they are more likely to buy online cart contents from physical stores [191]. Findings of the studies showed that privacy policies and security measures within online stores positively influence perceived trustworthiness of online stores [95, 188]. Perceived fairness of the return policy is positively associated with both consumers’ trust in online retailers and their intention to make purchases from their online stores [197]. It was also found that free delivery and return policies increase the number of order made over online stores [196]. The study conducted in Singapore by Xie et al. [190] showed that online consumers tend to provide accurate personal information in the presence of privacy notices within online stores. Even though they found positive relationship between the presence of privacy notices within online stores and consumers’ intention to provide accurate personal information, they stressed that the nature of this relationship may vary according to the political, economic, legal and cultural contexts [190].

It was found that reputation of the company or online store is positively associated with consumers’ provision of accurate personal information [190]. While Wang and Lang [89] found that company’s reputation affects consumers’ initial trust belief toward online seller, Utz et al. [198] did not find any significant relationship between these factors. Kim and Lennon [199] showed that when online sellers’ reputation is high, consumers’ hold more positive emotions and less perceived risk toward online sellers.

Online Shopping Tools

Studies classified under this category attempt to assess the influence of online shopping tools on online consumer shopping behavior. Shopping tools assessed by researchers includes recommender agents [16, 18, 203, 204, 205], avatars [206], image interactive technologies [70, 207, 208], social presence tools [209, 210], search tools [181, 182] and communication tools such as online consumer reviews [211]. Recommender agents are information filtering technology which provides high-quality product recommendations for the online consumers. There are several types of recommender agents, namely, collaborative filtering, knowledge-based, content-based, demographic, hybrid, etc. Yoon et al. [16] and Hostler et al. [204] showed that the use of collaborative filtering systems positively influences product recommendation quality, product promotion effectiveness and product search effectiveness. Recommendation quality and product promotion effectiveness, in turn, have a positive effect on consumers’ satisfaction with their shopping experiences at retailers' online stores. Furthermore, Lin and Chuan [170] found that knowledge-based recommender agents improve the decision making process by reducing decision making duration and effort in online stores. Keeling et al. [206] utilized avatars (i.e., interactive animated characters) to play the social role of a sales assistant. Their study tested whether avatars with social- or task-oriented communication styles contribute to consumer trust and patronage intentions. Results of the study showed that both types of communication styles directly and positively related to consumers trust and patronage intention toward online merchants’ websites. Bae and Lee [211] showed that online consumer reviews can be utilized as a powerful communication tool to reduce consumers’ uncertainty and perceived risk of buying products from online retailers.