No open-access location is known for this record yet.
No open-access location is known for this record yet.
INTRODUCTION The evaluation of internet shopping behavior has been ongoing for nearly 20 years, beginning in the mid-1990s when online retail sales were mostly considered to be a novelty venue, and continuing through present times. In 2013, total U.S. e-commerce retail sales were in excess of $260 billion which reflects a change of approximately 3.5% from the prior year (U.S. Census Bureau News 2014). Driving the growth are two factors: 1) increased use of smart phones and tablets, which are being used to research purchases and find the best price; and 2) traditional retailers' increased investment in their online businesses. Interestingly, growth is not originating from new customers. Instead, growth is being driven by existing online shoppers who are gradually moving from low consideration goods to more sophisticated products (Forrester Research Online Retail Forecast, 2012-2017 [U.S.]). The theory of why consumers do or do not shop online has been examined carefully as the medium has grown exponentially. At the very lowest level, McGuire (1974) suggests that all shopping motivation is primarily driven by individual gratification and satisfaction. A 2005 review of the literature on online consumer behavior reports that three theories have played dominant roles: theory of reasoned action, expectation-confirmation theory, and innovation diffusion theory (Cheun, Chan, & Limayem 2005). Each of these theories is helpful in understanding consumer behavior at different stages from intention to adoption to repurchase. Limayem, Khalifa and Frini (2000) hypothesized that internet shopping could be explained by specific behavioral theories such as Fishbein and Ajzen's (1975) theory of reasoned action or Ajzen's (1991) theory of planned behavior. Monsuwe, Dellaert and Ruyter (2004) using the technology acceptance model showed that attitudes toward online shopping were affected by ease of use, usefulness, consumer traits, situational factors, product characteristics, trust, and previous online shopping experience. More recently, Gupta and Kim (2010) used mental accounting theory to investigate internet shopping. Under this theory, customers evaluate potential transactions and then approve or disapprove each potential transaction. Factors, such as risk, pleasure, and convenience, determine the perceived value of the transaction and therefore, determine the intention to purchase online (Gupta and Kim 2010). The growing body of literature indicates that the drivers of online shopping can be divided into five categories: consumer characteristics, product/service characteristics, medium characteristics, merchant characteristics, and environmental influences. Early explanations for the determinants of online shopping behavior varied widely but were broadly classified as relating either to specific consumer motivations/traits (or some aspect of the consumer), features of the online medium, and, in some cases, a combination of both. Pachauri (2002), for example, classified the determinants into the following four concepts: (1) minimization, i.e., consumers are searching for the best product at the lowest price and they shop online when the time to accomplish this is minimized; (2) risk minimization, i.e., again, since consumers want to optimize decision-making regarding price and quality of products, they shop online where merchant reliability, credibility, and trustworthiness are not significant deterrents; (3) consumer lifestyle, i.e., shopping behavior is a function of one or several consumer variables such as sociodemographics, buying motives and needs, and attitudes, interests, and opinions; and (4) influence, i.e., online shopping behavior can be driven by contextual factors such as website atmosphere and site accessibility. Khalifa and Limayem (2003) reported the key influences on intention to shop online includes perceived consequences, specifically cheaper prices; facilitating conditions, such as transaction efficiency; and social influences of family and media. …
Loading…
Stored only when both papers are in the corpus — 4 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.