How Motivation Influences Online Shopping Report

A Typology of Online Shoppers Based on Shopping Motivations

Past research on consumer motivation focuses on the reasons that consumers shop online. Several theories give reasons for the behavior, but there is little empirical evidence. Currently, consumers get information quickly due to fast links between most product dealers within the supply chain. As such, it is paramount for organizations to form consumer relationships on the internet. Hence, consumers end up paying lower prices for some products while others are willing to pay severe prices. Consumer motivation might be a reason for the discrepancy in prices (Rohm & Swaminathan, 2004).

The Scope and Objectives of the Paper

This research aims at establishing a typology of online customers that is derived from online shoppers. There is a wide variety of shopping typologies already developed for store and catalog settings. However, there is a lack of research that examines typologies in the online arena (Rohm & Swaminathan, 2004). As such, this paper provides the basis for the identification of the different consumer segments and develops targeting strategies.

Methodology

This research engages a random sample of 1000 potential respondents consisting of both active and lapsed customers of an online grocery retailer (Rohm & Swaminathan, 2004). Only 25% of the mailed surveys were usable for the study. The researchers then drew a sample from offline customers to gain an insight into the motivations. Approximately a third of the respondents sent back the surveys; thereafter, they used demographic characteristics to match the online and offline samples (Rohm & Swaminathan, 2004).

Major Findings

The resultant topology, a four-group typology, was developed using cluster analysis that was based on analysis of factors. A cross-validation procedure was then employed to test the reliability of the solution, and shopping types were established (Rohm & Swaminathan, 2004). They are:

• The Convenience Shopper (Cluster 1: 10%): This group shows minimum physical store orientation, as well as variety-seeking behavior across retail channels.
• The Variety Seeker (Cluster 2): This group comprising about forty percent of the sample is moderately motivated by shopping convenience, but more so by variety-seeking across retail alternatives and products and brands.
• The Balanced Buyer (Cluster 3): In this cluster, about a third of the sample was moderately driven by the desire to seek variety. They exhibit a desire for convenience and a low tendency to plant the shopping task and seek information.
• The Store-Oriented Shopper (Cluster 4): This cluster, about 15% of the sample, exhibits the lowest level of online shopping convenience. They also rate the highest on physical store orientation (Rohm & Swaminathan, 2004).

The implication for Consumer Behavior Theories and Practices

The study showed, as in previous studies, that overall shopping experience and desire for social interaction are still as relevant motives for shopping in the online context as they are in the offline context. Online shopping also offered consumers an opportunity to compare and contrast. This greatly enhanced variety-seeking behavior. From the offline sample, there are three distinct clusters of offline shoppers: recreational, functional, and time-conscious shoppers (Rohm &Swaminathan, 2004).

Limitations

Extrinsic Versus Intrinsic Motivations for Consumers to Shop On-Line

Companies have increasingly used the internet as a channel to provide information and make direct sales to consumers. However, online sales continue to lag behind offline sales figures. Therefore, the adoption explains the perceived reliability and ease of use of the internet in comparison to normal shopping. Extrinsic motivations, like these, interact well with intrinsic motivations like perceived enjoyment and social activity, which are generally lacking in on-line shopping (Shang, Chen &Shen, 2005).

The Scope and Objectives of the Paper

This paper will determine both intrinsic and extrinsic factors that determine a shopper’s decision to shop online rather than a brick and mortar store. It will explain the perceived usefulness, ease of use, and convenience that online shopping brings. Although less entertaining than brick and mortar shopping, online shopping has grown over the years and this paper will explain the new entertainment methods that companies are using to lure more consumers to them (Shang, Chen & Shen, 2005).

Methodology

In this study, measuring scales to measure the hypotheses were developed using prior studies whenever possible. Real online shopping behavior was determined by asking whether the respondent had transacted on-line and by using a different scale for the intensity of on-line shopping (Shang, Chen & Shen, 2005). Items for perceived ease of use and for perceived usefulness to online consumers were subsequently developed. A scale of the multi-dimensional construct cognitive absorption and a scale for fashion involvement were also added (Shang, Chen & Shen, 2005).

Major Findings

The studies also found evidence contrary to previous assumptions that online shopping was goal-oriented. Researchers discovered intrinsic motivations to be the primary motivations for online shopping while extrinsic motivations were not as prominent as expected (Shang, Chen & Shen, 2005). This was true for models explaining online shopping intensity and the decision on whether to shop online or not.

The implication for Consumer Behavior Theories and Practices

The study of the effects of intrinsic and extrinsic motivations also resulted in evidence contrary to previous assumptions that online shopping was goal oriented. Intrinsic motivations were found to be the primary motivations for online shopping while extrinsic motivations were not major (Shang, Chen & Shen, 2005).

Limitations

Although previous research had always assumed that online shoppers knew what they wanted when they set out to shop, this study found empirical evidence to the contrary. This appears to negate other researchers’ findings. This was also true for intensity and frequency. Hence, this was a step behind in trying to generalize findings on online shopping behavior. The researchers did not use random sampling in selecting objects for the sample further reducing the generalize-ability of the findings (Shang, Chen & Shen, 2005).

Conclusion

The study found evidence contrary to previous assumptions that online shopping was goal-oriented. They also found intrinsic motivations to be the primary motivations for online shopping while extrinsic motivations were not a strong influence as previously thought. Brick and mortar shopping still had major advantages over online shopping because it was associated with fun, entertainment, and social interactions. Hence, online shopping needed a boost in terms of motivating the shopper (Shang, Chen & Shen, 2005).

The Influences of Shopping Motivation on Adolescent Online-Shopping Perceptions

Online retailers competing among themselves and against the traditional brick and mortar stores have also developed an interest to explore consumer motivation that makes them shop online. The growth in online shopping has also coincided with the excellent uptake of internet usage by young adults. Marketers are keen to develop adolescent profiles on internet usage and develop relevant strategies. This paper will leverage these profiles on adolescents’ shopping motivations and perceptions and the relationship between the two (Chang, Lai & Wu, 2010).

The Scope and Objectives of the Paper

The paper will investigate the specific relationships between adolescents’ online shopping perceptions and the six major motivations to shop online. These motivators include social interaction, role accomplishment, and choice optimization among others. The study also seeks to determine the motivations underlying the typical young web consumer. This will help online marketers to profile the characteristics that constitute the different market segments to help in developing strategies (Chang, Lai & Wu, 2010).

Methodology

The practical and hedonic views of adolescents toward online shopping and their effects on motivations were investigated using web questionnaires administered to a sample consisting of adolescents who had prior online shopping experience. The questionnaire was designed to measure four concepts, all revolving around motivation as a cause of online shopping (Chang, Lai & Wu, 2010). The revised motivations include social interaction motivation, sensory stimulation motivation, r, ole enactment motivation and emotional utility motivation. The dimension and validity were the four constructs were confirmed by confirmatory and exploratory factor analysis (Chang, Lai & Wu, 2010).

Major Findings

The study explored the motivations affecting adolescents’ online behavior. The researchers found that adolescents’ shopping motivations were strongly related to shopping perceptions (Chang, Lai & Wu, 2010). This is true for all except for economic utility motivation. They discovered that there is a relationship between Hedonic perception, social interaction, and emotional utility while utilitarian perception had a positive relationship to motivations of sensory stimulation, role enactment, and choice optimization. This partly confirmed earlier studies, which had used a more representative sample of all adults (Chang, Lai & Wu, 2010).

The implication for Consumer Behavior Theories and Practices

Sellers should develop appropriate ways of providing product and service information and find ways to vend goods effectively goods and services on However trivial the relationship between motivations and internet usage seem, they are still relevant (Chang, Lai & Wu, 2010). Vendors of products online should also strive to increase the interactivity of their WebPages to increase consumer interactive control motivations. Consumers will derive significant satisfaction from using the online solution offered. Vendors should encourage the development of social relationships with their customers (Chang, Lai & Wu, 2010).

Limitations

The samples employed in the study were also not representative. Despite students making up the bulk of internet users, they do not represent the majority of users who have less shopping time and higher disposable incomes. The sample selected in some studies was also too small and non-representative of the population. This is likely to lead to inaccurate generalizations from the extrapolation of the results of the findings (Chang, Lai & Wu, 2010).

Conclusion

Researchers found a strong relationship between adolescents’ shopping motivations and shopping perceptions. This is true for all except for economic utility motivation (Chang, Lai & Wu, 2010). There is a positive relationship between hedonic perception and social interaction and emotional utility and another positive relationship between utilitarian perception and motivations of sensory stimulation, role enactment, and choice optimization. Marketers can use these findings to understand shopping motivations and hence develop a segmentation strategy (Chang, Lai & Wu, 2010).

Exploring Motivations for Consumer Web Use and Their Implications for E-Commerce

Consumer web behavior is defined by two activity levels i.e. the percentage of total browsing time spent getting information about products and the frequency of purchases made on the Web. The factors mentioned above are measured against the findings of these two determiners.

The Scope and Objectives of the Paper

The study also seeks to determine the motivations underlying the typical web consumer. Consumer web behavior is defined by two activity levels i.e. the percentage of total browsing time spent getting information about products and the frequency of purchases made on the Web. The factors mentioned above are measured against the findings of these two determiners. The paper also investigates the ever-changing demographics of internet users (Joines, Clifford & Dietram, 2003).

Methodology

The selection process was conducted in three phases. The first one selected a sample of 300 people from over 1600 people, who proceeded to the second phase. Finally, 60 people participated in the study, and 59 responded to the questionnaires. Data was collected aimed at the final findings. The independent variable was web consumer, dependent variables were time spent learning about products, and the number of items actually bought online. Using least-squares-multiple-linear-regression-analysis, the data were analyzed (Joines, Clifford & Dietram, 2003).

Major Findings

Users who spent more time researching products and services generally had larger financial motivations while those who feared for their security spent less time searching for information. The study’s findings did not support the motive to search for information and information search. Information loads are also determining factors in online shopping (Joines, Clifford & Dietram, 2003). Gender and age were other determiners of consumer web use. Consequently, younger people were more likely to shop online just as females (Joines, Clifford & Dietram, 2003).

The implication for Consumer Behavior Theories and Practices

The online shopping context was characterized by consumers seeking variety seeking and motivated by convenience (Joines, Clifford & Dietram, 2003). However, the offline shopper was more motivated by timesaving and recreation when compared to the typical online shopper. Therefore, these factors may be used in differentiating shopping types across these channels and in developing a model of online shopping motivation (Joines, Clifford & Dietram, 2003). The research also contributes to the knowledge of Internet marketing. Retailers should therefore seek to develop strategic alliances for such products and services (Joines, Clifford & Dietram 2003).

Limitations

Researchers believe that web research has sampling biases. Hence, some portions of the population may have been overrepresented. This study used a relatively high significance level value. This reduced the confidence level of the research. Additionally, the sample used was quite small and targeted educated well-off males. This over-represents part of the population, which reduces the generalizability of this research (Joines, Clifford & Dietram, 2003).

Conclusion

The study found that motivation matters. This means that sellers should devise new ways to encourage and motivate online shopping. For example, a good product-information display on the internet (Joines, Clifford & Dietram, 2003). Additionally, sellers should improve transactional privacy as these features as the major concern for an online shopper.

The Impact of the Internet and Consumer Motivation on Evaluation of Prices

Online shopping has grown tremendously over the years. Hence, considerable interest has been aroused among many researchers. The researchers are keen to determine the relationship between the online shopping environment and consumer choice. The researchers have also studied the possible relationships between online shopping and price movements (Suri, Long & Monroe, 2003).

The Scope and Objectives of the Paper

The paper seeks to establish whether customers pay well when they purchase online products. Additionally, the paper seeks to establish the effect of motivation and its influence on prices. As such, this paper tries to establish whether there is a relationship between internet selling and the price level (Suri, Long and Monroe 2003).

Methodology

The main premise was based on the fact that most web users have some college education (Suri, Long and Monroe 2003). Approximately 90% of the 218 responses received were usable for the purposes of the study. Thereafter, the subjects were allocated randomly to the eight action conditions. The association between price and three dependent variables: perceived sacrifice, perceived value, and perceived quality was investigated with the influence of motivation (Suri, Long & Monroe, 2003).

Major Findings

An increase in information loads resulted in increased consumers’ perceptions of quality and value, but with a decrease in the level of sacrifice (Suri, Long & Monroe, 2003). As a result, users should be willing to pay higher rates when they have a higher perception of product value.

The implication for Consumer Behavior Theories and Practices

As a consequence, online retailers must represent their products in such a way that low price will not be associated with low sacrifice rather than low quality. They should balance between information loads so as to increase the exposure of their products. This can be implemented by establishing an accurate target market by using recent technology (Suri, Long & Monroe, 2003).

Limitations

It is hard to measure motivation levels. The tests that the study used may not reflect as accurately the motivation levels of the entire population. In addition, information loads are different in diverse settings (Suri, Long and Monroe 2003). What one consumer wants may differ from what another consumer wants. This difference in information needs may not have been factored in the study. These factors may limit the generalize-ability of the conclusions (Suri, Long and Monroe 2003).

Conclusion

As established, online retailers must represent their products in such a way that low price will not be associated with low sacrifice. This will ensure that the whole marketing procedure is successful.

References

Chang, M., Lai, M. & Wu, W. (2010). The Influences of Shopping Motivation on Adolescent Online-Shopping Perceptions. African Journal of Business Management, 4.13: 2728-2742. Web.

Joines, L.J., Clifford, W.S. & Dietram, A.S. (2003). Exploring Motivations for Consumer Web Use and Their Implications for E-Commerce. Journal of Consumer Marketing, 20.2: 90-108. Web.

Rohm, A.J. & Swaminathan, V. (2004). A Typology Of Online Shoppers Based On Shopping Motivations. Journal of Business Research, 57(1): 748-757. Web.

Shang, R., Chen, Y. & Shen, L. (2005). Extrinsic Versus Intrinsic Motivations for Consumers to Shop On-Line. Information & Management, 42: 401–413. Web.

Suri, R., Long, M. & Monroe, K.B. (2003). The Impact of the Internet and Consumer Motivation on Evaluation of Price. Journal of Business Research, 56.1: 379-390. Web.