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Attitude and behavior towards internet shopping

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Studies on factors determining consumer attitude and behavior towards Internet shopping:

Most of the studies conducted in the recent years in field of online shopping behavior and attitude have been focusing on the factors influencing the online shopping attitudes and behavior. But, different researchers have diverse opinions and focus, while studying the impact of these factors on the online consumer buying behavior and attitudes. For example, there is a segment of researchers who have tried to explain the consumer attitude and intentions for online shopping by taking theories like Theory of Reasoned Action, Technology acceptance model or Theory of Planned Behaviour as a basis and have tried to extend them further by adding more web specific factors to them(Cheung, Zhu, Kwong, Gloria, and Limayem, 2003), whereas there has been another segment who have derived relationships between various factors and customer satisfaction with reference to the Internet shopping experience in the form of dependent and independent variables. Further, there have been researchers who have further organized and compiled the previous researches done in this field so as to pave way for future researches. These researchers have also contributed in terms of designing structured frameworks for online consumer attitude, intention and buying behavior.

Web experience

The literature review done by Constantinides (2004) helps in identifying the web experience components and their role as the first step in shaping the online consumer’s behavior. He has added web experience as a controllable element in his model depicting factors that influence the online buying behavior. He has further explained web experience factor by classifying it in three sub-categories which are the building blocks of the web experience. These three sub-categories are Functionality factors (usability and Interactivity), Psychological factors (trust) and Content factors (aesthetics and Marketing Mix). The following figure as adopted from his article presents a brief description of the number of references in support of each of these factors:

Source: Constantinides, E.(2004). Influencing the online consumer’s behavior: the web experience. Journal of Internet Research. Vol 14 No.2, pp. 114, figure 2.

Literature review

Li and Zhang (2002, p.508) have defined online buying behavior or Internet shopping/buying behavior as “the process of purchasing products or services via the Internet”; which according to Liang and Lai (2000), is similar to the traditional five steps process of consumer buying behavior (as cited by Li and Zhang, 2002). They have also defined online shopping attitude as the psychological state of the consumers in terms of Internet shopping (2002). Li and Zhang (2002) have analysed 35 empirical studies on online shopping attitudes and behavior conducted during the period of January 1998 to February 2002 and have finally identified 10 inter-related factors for which the reviewed studies have significant empirical evidences. These 10 factors have further been classified into five independent factors (viz. external environment, demographics, personal characteristics, vendor/service/product characteristics, and website quality) and five dependent factors (viz. attitude towards online shopping, intention to shop online, decision making, online purchasing, and consumer satisfaction.)

Another exhaustive literature review in this field has been by Cheung et al. (2003). They have examined a total of 351 articles in the area of online consumer behavior from 1994 to April 2002. They have attempted to link together the concepts of intention, adoption and continuance and form a base model- a Model of Intention, Adoption and Continuance (MIAC) for the development of an online consumer behavior framework. Further, the various factors as mentioned by various researchers in their study have been categorized under five major domain areas viz. individual/consumer characteristics, product/service characteristics, medium characteristics, and online merchant and intermediary characteristics. According to them, online purchase intention and adoption has been extensively studied and there are lots of empirical evidences available, but research on continuance or consumer online repurchase is in its infancy. The following figure describes the MIAC model as suggested by Cheung et al.

Framework of online consumer behavior

Source: Cheung, C.M.K., Zhu, L., Kwong, T., Chan, G.W.W. & Limayem, M.(2003). Online Consumer Behavior: A Review and Agenda for Future Research. Proceedings of the 16th Bled eCommerce Conference, eTransformation. 194-218

A recent study conducted by Kuczmarski and James (April 2008) further contribute to the available body of literature by adding that consumers prefer online stores to actual stores due to potential reasons like convenience, cost and selection.

Trust as a factor

Studies also indicate that trust remains a crucial factor in e-commerce and in influencing the purchase decision of online shoppers. Consumers prefer to shop from trusted websites. Researches reveal that trust is a factor which also helps in forming long-term customer relationships (Dwyer, Schurr & Oh, 1987; Gefen & Straub, 2003; Kim, Xu & Koh, 2004). Some researchers like Lee (2002), Liebermann and Stashevsky (2002), McKnight et al.(2002), Suh and Han(2002) and Liang and Lai(2002) have even argued that a new step has been added to the online buying process and that is the step of building trust or confidence (as cited by Constantinides, 2004). The available literature explains that trust facilitates e-commerce and online transactions, but at the same time the consumer’s lack of trust in online vendors continues to remain a hindrance in the growth of e-commerce. (Ba & Pavlou, 2002; Gefen and Straub, 2003; Gefen, Karahanna & Straub, 2003; Kim, Xu & Koh, 2004; Lim, Sia, Lee & Benbasat, 2006; Pavlou & Gefen, 2004). Gefen(2002) and Kim, Xu & Koh (2004) have stated that a key challenge to e-commerce is that creating trust typically requires multiple interactions and superior service over a period of time(as cited by Lowry et al., 2008).

Brand has also been established as one of the factors influencing the customer trust for a website (Bart, Shankar, Sultan & Urban, 2005; Yoon, 2002). Ward and Lee(2000) conducted a research to examine whether consumers use brands as sources of information when shopping on Internet and they concluded that branding can facilitate consumers’ acceptance of e-commerce. Lowry, Vance, Moody, Beckman & Read (2008) have studied the impact of “branding alliances and web-site quality” on the consumer trust of e-commerce websites. They explored the usage of branding alliances and website quality by the less familiar websites to enhance the consumer trust and suggested that branding and web-site quality can significantly increase the initial consumer trust in the e-commerce websites.

Ballantine(2005) has studied the effects of interactivity and the amount of product information provided by an online shopping environment on consumer satisfaction. A web-based experiment was conducted where respondents were exposed to a simulated online retail store. Findings indicate that these two factors had a significant effect on the consumer satisfaction.

Tangibility also remains an important factor in influencing the purchase process of Internet shoppers. Melian-Alzola and Padron-Robaina(2006) have analysed the role and importance of the tangible elements of purchase processes in business to consumer(B2C) e-commerce, and the impact on overall perceived quality and the customers’ attitudes. Their research concluded that that four attributes – navigation, signposting, tools and explanation – explain the tangible dimension in electronic commerce. They revealed that design was an important factor of overall perceived quality and the willingness to recommend the purchase experience to others.

Security of transactions is another factor that remains as a matter of concern for e-commerce consumers. According to a study conducted by American Banker in 2007, one-third of Canadians refused to shop online due to fear of identity theft. Web assurance services help in building up the trust and confidence of such consumers.

In an experimental study undertaken by Mauldin and Arunachalam (2002), the impact of web assurance services and retailer disclosures on purchase intent was studied. They have defined web assurance as the measures taken to reduce information risks and increase online purchasing by improving the reliability of certain information on the website. Their findings indicate that web assurance. In this research they considered TRUSTe, WebTrust and VISA web assurance services for the study. Their findings indicate that there were no significant differences in intent to purchase among the three assurance providers. Mauldin and Arunachalam have also studied the impact of product and retailer familiarity on the buying behavior of online consumers in the above mentioned study and they suggest that web assurance is insignificant when product familiarity is higher, or in other words, where product familiarity is lower, intent to purchase is higher with web assurance. Retailer familiarity is not found to be significant in any of the conditions. Further, their study also reveals that retailer disclosures are sufficient to impact buying intention of online consumers; the web assurance services studied in the above study did not provide any additional assurance beyond the retailer disclosures. They have further emphasized that comfort with the Internet, general intent to buy online, and website design played significant role in influencing purchase intention. Although security is a major concern of online buyers, their study indicates that information risk generally did not significantly influence purchase intention, which explains why web assurance is generally not significant in their study.

Bruce, Katherine and Murphy (2008) have further explored the prior studies on web assurance models to provide detailed explanation on current reporting requirements, differences among web assurance services and perceptions of consumers regarding these services. The study concludes that consumers give importance to web assurance services, but younger consumers place greater value on these services rather than older consumers.

Technology Acceptance Model as a basis for research on

Literature review

In an attempt to design a structured framework for the effects of different factors on “consumer attitude towards Internet shopping and their intentions to shop online”, Monsuwe, Dellaert and Ruyter (2004) have reviewed the various researches conducted in the field. They have used Technology Acceptance Model (TAM) as a base and suggested a framework based on previous research on consumer adoption of new technologies and services. The Technology Acceptance Model (Davis, 1989) has served as a basis for various researches conducted in the Information systems field. In order to support the selection of TAM as a basis for their research work, Monsuwe et.al, 2004 have cited Chen et al.(2002), Moon and Kim(2001) and Lederar et al.(2000) who suggest that although this model is specifically designed to understand the adoption of a new computer – based technology in the job/workplace, it has also proven to be suitable as theoretical foundation for adoption of e-commerce as well. The Technology Acceptance Model (TAM) suggests the “usefulness”, “ease of use” and the later addition of “enjoyment” (Davis et al., 1992) as the determinants of consumers’ attitude towards adopting a new technology. This attitude, further, has a strong and positive effect on consumers’ intentions to actually use the new technology or system (Bobbitt and Dabholkar, 2001; Davis, 1993). While redefining the three constructs in context of online shopping Monsuwe et.al.(2004, p.107) have referred to “usefulness” as the “consumers’ perceptions that using the Internet as a shopping medium enhances the outcome of their shopping experience”. Similarly, they have redefined “ease of use” as the consumers’ perception that the process leading to online shopping will require minimum effort and will be easy. Further, according to them, the “enjoyment” construct refers to the fun and playfulness of the Internet shopping experience. While “usefulness” has a weak direct link to attitude, it shows a strong direct link towards intention to shop online (Davis et al., 1989). It is also linked with “ease of use” to determine consumers’ attitude towards online shopping. Hence, “ease of use” has a direct as well as indirect effect on consumers’ intention to shop online.

Using TAM as a basis for the study, the framework proposed by Monsuwe, Dellaert and Ruyter(2004) not only includes the functional/utilitarian and hedonic dimensions like “ease of use”, “usefulness”, and “enjoyment” which affect the consumers’ attitude and intention towards Internet shopping, but they have also included some of the exogenous factors recommended by various researchers in the framework such as “consumer traits”(Burke, 2002; Dhabolkar and Bagozzi, 2002; Brown et al., 2001; Eastin and LaRose, 2000), “situational factors”(Wolfinbarger and Gilly,2001; Avery, 1996), “product characteristics”(Grewal et al., 2002; Elliot and Fowell, 2000), “previous online shopping experiences”(Shim et al., 2001; Eastlick and Lotz, 1999) and “trust in online shopping”(Yoon, 2002; Lee and Turban, 2001)

Monsuwe et.al. in their research, have mentioned about the various researches done in order to extend the TAM by suggesting additional factors. For example, Venkatesh (2000), who has proposed integrating factors like “control”, “intrinsic motivation”, and “emotion” into the existing Technology Acceptance Model which are considered to be strong determinants for “ease of use” construct of TAM. Dabholkar and Bagozzi (2002) have given an attitudinal model of technology based self-service by suggesting two exogenous factors like “consumer traits” and “situational influences”. Further, they have cited O’Cass and Fenech (2002) who have added seven key consumer characteristics namely “opinion leadership”, “buying impulsiveness”, “satisfaction with websites”, “web shopping compatibility”, “shopping orientation”, “Internet self-efficacy”, and web-security” to the model.

Further, they have substantiated their model by citing the classification given by Hirschman and Holbrook (1982) who have categorised Internet shoppers in two categories; one is of the “problem solvers” and other category is of those seeking for “fun, fantasy, arousal, sensory stimulation, and enjoyment”. Monsuwe et al. suggest that this classification also supports the basic three constructs of TAM which affect the consumers’ attitude towards Internet shopping as “ease of use” and “usefulness” reflect the utilitarian aspect and “enjoyment” is in sync with the hedonic aspect of the model.

The above explanation given by Monsuwe et al. is similar to the categorization of the shopping orientations by Bellenger, Robertson and Greenberg(1977) as convenience versus recreational orientation (as cited by Kim, LaRose, 2004)

Various researches have been conducted to identify the underlying dimensions for the basic constructs of the TAM model. These latent dimensions can be further used to understand how these constructs get influenced by various exogenous factors. For example, Mathwick et al. (2001) have added two interesting latent dimensions to the “usefulness” construct” “Consumer Return on Investment(CROI)”, and “service excellence”. Monsuwe, Dellaert and Ruyter (2004) have defined “CROI” as a “perceived return on cognitive, behavioural or financial investment made by the consumer.” Whereas, “service excellence” evaluates the delivered promises against the performance. If both these dimensions are satisfied, then consumers will judge the Internet shopping performance positively (Mathwick et al., 2002) which adds to the perceived “usefulness”. Zeithamal et al. (2002) have stated that “site characteristics” such as search functions, download speed and navigation also acts as a determinant in shaping “ease of use” construct of the TAM model. But, Monsuwe et al. (2004, p.109) have a different opinion regarding this dimension. They have stated that “…these site characteristics merely influence the “ease of use” of a particular web site or online store, and not the Internet as a shopping medium in general…”

Online Shopping orientations

Kim and LaRose (2004) have defined shopping orientation as a shopper’s attitude toward shopping activity that may vary with the situation rather than an invariant personality trait of the shopper. They have cited the categorization given by Bellenger, Robertson and Greenberg (1977) which classifies shoppers on the basis of their shopping orientation into convenience versus recreation oriented. Kim and LaRose (2004) also posit that shoppers may possess multiple orientations depending upon the expected outcome of a shopping experience and may demonstrate a regulated/utilitarian or an unregulated/recreational shopping orientation depending upon the environmental stimuli. Their study also shows that these two shopping orientations are not mutually exclusive and interactive web features may draw shoppers with convenience orientation into unregulated buying.

Li, Kuo and Rusell(2006) have also studied the impact of shopping orientations on online consumer behavior alongwith other factors like demographics, channel knowledge and perceived channel utilities. Primary data was collected by a research company using an online survey of 999 U.S. Internet users. They have classified Internet users as frequent, occasional and non-buyers. Findings indicated that frequent web buyers have a higher degree of perceived channel utility for the purpose of communication, distribution and accessibility. Similarly channel knowledge also has a positive effect on the Internet buying and it also has a reciprocal influence on the perceived channel utilities. Their study also indicates that frequent web buyers value convenience more than experience(touch and feel of the product) whereas those who are non-web buyers have a higher degree of experience orientation. Recreation and economy orientation are found to be similar for the three types of Internet buyers. The study of the demographic factors revealed that male are more frequent web buyers than women, better-educated consumers shop more frequently online and consumers with higher income are more likely to be in frequent web buyer category. Age was not significant as far as frequency of web buying was concerned.

Note: Most of the researchers feel that the classical consumer behavioral theories used for can only act as a starting point for understanding the online consumer behavior. There is no structured framework for explaining the online consumer behavior; the studies are mostly fragmented. Researchers have suggested different factors and frameworks, but there is a lack of a cohesive theoretical base to the online consumer behavior.

Ba, S.L., and Pavlou, P.A. Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 26, 3 (2002), 243-268.

Gefen, D., and Straub, D.W. Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services. Omega: The International Journal of Management Science, 32, 6 (2004), 407-424.

Gefen, D.; Karahanna, E.; and Straub, D.W. Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27, 1 (2003), 51-90.

Kim, H.-W.; Xu, Y.; and Koh, J. A comparison of online trust building factors between potential customers and repeat customers. Journal of the AIS, 5, 10 (2004), 392-420.

Lim, K.H.; Sia, C.L.; Lee, M.K.O.; and Benbasat, I. Do I trust you online, and if so, will I buy? An empirical study of two trust-building strategies. Journal of Management Information Systems, 23, 2 (Fall 2006), 233-266.

Pavlou, P.A., and Fygenson, M. Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30, 1 (2006), 115-143.

Dwyer, F.R.; Schurr, P.H.; and Oh, S. Developing buyer-seller relationships. Journal of Marketing, 51, 2 (1987), 11-27.

Everard, A.P., and Galletta, D.F. How presentation flaws affect perceived site quality, trust, and intention to purchase from an online store. Journal of Management Information Systems, 22, 3 (Winter 2005-6), 56-95

Kuczmarski, James (2008, Apr). JOURNAL-IST: Freedom of Choice. Fast Company, Issue 124, 43-43, 1/2p

Runyan, B., Smith, K.T., Smith, L. M.(2008, Mar). Implications of Web assurance services on e-commerce. Accounting Forum (Elsevier), Vol. 32 Issue 1, 46-61

Gefen, D. Customer loyalty in e-commerce. Journal of the AIS, 3, 1 (2002), 27-51.

Bart, Y.; Shankar, V.; Sultan, F.; and Urban, G.L. Are the drivers and role of online trust the same for all Web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 69, 4 (2005), 133-152.

Yoon, S.-J. The antecedents and consequences of trust in online-purchase decisions. Journal of Interactive Marketing, 16, 2 (2002), 47-63.

Lowry, P.B., Vance, A., Moody, G., Beckman, B. & Read, A. (2008). Explaining and Predicting the Impact of Branding Alliances and Web Site Quality on Initial Consumer Trust of E-Commerce Web Sites. Journal of Management Information Systems / Spring 2008, Vol. 24, No. 4, pp. 199-224.

American Banker(2007, 17 Dec), Vol. 172 Issue 241, p17-17, 1/9p

Monsuwe, T.P., Dellaert, B.G.C. & Ruyter, K.D.(2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management.Vol.15 No.1, pp.102-121

Ward,M.R. & Lee, M. J.(2000). Internet shopping, consumer search and product branding. Journal of Product and Brand Management, Vol.9 No.1, pp.6-20

Ballantine, P.W.(2005). Effects of interactivity and product information on consumer satisfaction in an online retail setting. International Journal of Retail & Distribution Management, Vol.33 No.1, pp.461-471

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Constantinides, E.(2004). Influencing the online consumer’s behavior: the web experience. Internet Research. Vol 14 No.2, pp. 111-126

Cheung, C.M.K., Zhu, L., Kwong, T., Chan, G.W.W. & Limayem, M.(2003). Online Consumer Behavior: A Review and Agenda for Future Research. Proceedings of the 16th Bled eCommerce Conference, eTransformation. 194-218

Li, H., Kuo, C. & Rusell, M.G.(2006, Jun). The Impact of Perceived Channel Utilities, Shopping Orientations, and Demographics on the Consumer’s Online Buying Behaviour. Journal of Computer-Mediated Communication. 5(2). Retrieved July, 1, 2009, from http://www3.interscience.wiley.com/cgi-bin/fulltext/120837782/HTMLSTART

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Abstract:

Customers in an Internet shopping environment actually play dual roles. One is the role as a customer in a shopping place, and the other is the role as a user of information technology. In both cases, the level of satisfaction is of great concern. In this vein, a way of measuring the satisfaction level that takes both roles into account is needed. However, in past research indexes for consumer satisfaction and indexes for user information satisfaction have been developed separately in the fields of marketing and management information systems. Because of this lack of interaction between the two streams of research, an index for electronic commerce consumers that has its base in the dual roles has not been developed and tested. In this research, an instrument for measuring electronic commerce consumer satisfaction was proposed and validated using a sample of over 400 customers. The relationship between the index and consumers’ purchasing intention was also examined.

Title:

Development of electronic commerce user-consumer satisfaction index (ECUSI) for Internet shopping

Author(s):

Namjae Cho, Sanghyuk Park

Journal:

Industrial Management & Data Systems

Year:

2001

Volume:

101

Issue:

8

Page:

400 – 406

ISSN:

0263-5577

DOI:

10.1108/EUM0000000006170

Publisher:

MCB UP Ltd

Abstract:

Purpose – The purpose of this study is to investigate the effects of consumers’ shopping orientation on their satisfaction level with the product search and purchase behavior using multi-channels.

Design/methodology/approach – A total of 181 students in a large US mid-western university provided usable responses to the survey. Exploratory factor analysis and multiple regression analyses were employed to examine the research questions.

Findings – The results showed that more than three quarters of the respondents shopped via the internet and catalogs, and about 95 percent shopped at non-local retailers. About 60 percent reported that they never shopped from TV shopping channels. Confident/fashion-conscious shopping orientation and catalog/internet shopping orientation were found to be key predictors of customer satisfaction level with information search via multi-channels. Both confident/fashion-conscious consumers and mall shopping-oriented shoppers were more satisfied with store-based retail channels for apparel purchases, whereas non-local store-oriented shoppers and catalog/internet-oriented shoppers were more satisfied with non-store-based retail channels for their apparel purchases.

Research limitations/implications – The sample of this study was biased by gender and age. For the apparel retail industry, this paper offers practical knowledge about the relationships between shopping orientation and consumer search and purchase behavior in a multi-channel retailing context.

Originality/value – No study has utilized the shopping orientation framework to explain consumer behavior in a multi-channel environment. This study provides understanding of consumer product information search behavior on four dimensions (price, promotion, style/trends, and merchandise availability) via multi-channels.

Title:

The effects of shopping orientations on consumers’ satisfaction with product search and purchases in a multi-channel environment

Author(s):

Hyun-Hwa Lee, Jihyun Kim

Journal:

Journal of Fashion Marketing and Management

Year:

2008

Volume:

12

Issue:

2

Page:

193 – 216

ISSN:

1361-2026

DOI:

10.1108/13612020810874881

Publisher:

Emerald Group Publishing Limited

Article Information:

Title:

Attitude toward internet web sites, online information search, and channel choices for purchasing

Author(s):

Yoo-Kyoung Seock, Marjorie Norton

Journal:

Journal of Fashion Marketing and Management

Year:

2007

Volume:

11

Issue:

4

Page:

571 – 586

ISSN:

1361-2026

DOI:

10.1108/13612020710824616

Publisher:

Emerald Group Publishing Limited

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Abstract:

Purpose – This study aims to examine the influence of attitudes toward particular clothing web sites, specifically favorite ones, on information search at those web sites and on the choice to purchase items from those web sites and from non-internet channels after finding the items at the web sites.

Design/methodology/approach – Using survey data from 414 US college students who had online shopping experience and favorite clothing web sites that they especially like to visit, hypothesized relationships among attitude toward internet web sites, online information search and channel choices for purchasing were tested using path analysis.

Findings – Results showed that participants’ attitudes toward their favorite clothing web sites had a direct, positive effect on their intentions to search for information at those web sites as well as intentions to purchase clothing items from those web sites after finding the items there. Additionally, operating through information-search intentions at the web sites, participants’ attitudes toward those web sites had an indirect, positive effect on their intentions to purchase clothing items from non-internet channels after finding the items at the web sites.

Research limitations/implications – Results cannot be generalized to the larger population of young consumers and to other consumer groups. Future research should include other population groups.

Practical implications – This research provides insights into how college students’ attitudes toward internet web sites affect their information search at the web sites and their channel choices for purchasing. Our results suggest potential benefits of multi-channel retailing for online clothing retailers targeting US college students and the importance of building effective web sites to elicit those consumers’ positive attitudes toward the web sites.

Originality/value – This study is the first to investigate young adult online shoppers’ attitude towards internet web sites and their information search and channel choices for purchasing.

Keywords:

Consumer behaviour, Information retrieval, Internet shopping, Purchasing, United States of America

Article Type:

Research paper

Article URL:

https://monkessays.com/write-my-essay/emeraldinsight.com/10.1108/13612020710824616

Article Information:

Title:

Do determinants of online shopping differ for personal shoppers and professional shoppers?

Author(s):

Amit Bhatnagar

Journal:

EuroMed Journal of Business

Year:

2007

Volume:

2

Issue:

1

Page:

87 – 102

ISSN:

1450-2194

DOI:

10.1108/14502190710749974

Publisher:

Emerald Group Publishing Limited

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