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While the popularity of online shopping has increased in recent years, surprisingly little research has examined the factors affecting consumers’ behavior in this context. Furthermore, though a widespread problem for companies, the phenomenon of online shopping cart abandonment has garnered even less attention. The purpose of this study is to examine the role of consumers’ mindsets in online shopping cart abandonment.

Three experimental studies were conducted to examine the effect of consumer mindsets (i.e. abstract vs concrete) on purchase intentions.

Results indicate that consumers who have an abstract (as opposed to concrete) mindset when shopping online rate the products they include in their shopping carts to be more important, and consequently are more likely to purchase them, reducing shopping cart abandonment.

The findings suggest that online retailers can reduce shopping cart abandonment by implementing strategies that allow consumers to think abstractly.

This research contributes to the literature by identifying an important underlying mechanism affecting online shopping cart abandonment.

The purpose of this study is to explore the factors leading to the consumer's propensity to abandon the shopping cart at the transaction completion stage.

Data were collected using a self‐administered survey distributed through the internet. The sample consisted of consumers who shopped online at least once during the preceding one‐year period.

The results indicate that perceived transaction inconvenience is the major predictor of shopping cart abandonment. The other predictors are perceived risk and perceived waiting time. Positive relationship was found between perceived transaction inconvenience, perceived risk and propensity to abandon the shopping cart. It was also found that propensity to abandon the shopping cart is negatively associated with the perception of waiting time.

The paper provides transaction completion stage specific guidance to the managers operating in an online environment to prevent shopping cart abandonment at the transaction completion stage. Specifically, the findings suggest that marketers must pay attention to the perception of risk and transaction inconvenience; otherwise they risk losing consumers during the final stage of transaction.

The paper examines the unexplored area of consumer behavior at the final stages of transaction culmination and, hence, is an initial step toward filling that gap.

Online cart abandonment is a severe issue posing challenges to e-commerce growth. Emerging economies such as India fascinates global marketing practitioners because of favorable demographics and high levels of internet penetration. This study aims to consider the role of certain exogenous factors in developing shopping motivations that sequentially mediate to online purchase completion through impulsiveness under risk perceptions. The primary motivation behind this study is to understand the mental mechanism among online customers that develop purchase completion intentions, which prevent cart abandonment significantly.

Impact of e-commerce exogenous factors related to e-commerce such as website attributes, product features, promotional excellence and decision-making easiness on shopping motivations, impulsiveness and purchase completions intentions under the moderating effect of risk was estimated from the perceptions of Indian online customers (n = 243) using variance-based structural equation modeling and SPSS process macro v.3.0.

The most important exogenous variable that can influence purchase completion directly, sequentially through shopping motivations is decision easiness and promotions. Even though utility motivations are dominant in purchase completion intentions, hedonistic aspects are more critical in developing impulsiveness. The translation of impulsiveness to purchase completion is happening, but risk perception significantly moderates impulsiveness formation.

Theoretically, this study examined online purchase completions being the most sought response by a customer to various stimuli in e-commerce. The study adopted a moderated mediation analysis in which shopping motivations and impulsiveness were mediators and risk as moderator. The interaction effect of risk on purchase completions was significant even when the mediating effects were prominent.

Contributes to the current knowledge-related online buying behavior in virtual retail formats and helps marketers in streamlining their focus in using impulsiveness as a strategic tool in reducing cart abandonment.

This study helps in understanding emerging trends in online buying behavior in India.

By integrating uses and gratification theory (UGT) and online buying behavior theory (OBBT), this study aims to examine the impact of escapism motives (self-suppression and self-expansion) and attitude toward online shopping (ATS) on eCart abandonment. In addition, the mediating role of ATS between escapism motives and eCart abandonment is examined.

Structural equations modeling was performed on the data of 400 consumers using AMOS 26.

The results indicated that escapism motivations impacted users’ eCart abandonment, and the attitude toward online shopping mediated this relationship.

The findings of this study imply that online sellers should understand the consumer motives for website use. In response, better strategies should be developed to reduce eCart abandonment.

This study extends knowledge of eCart abandonment by theoretical integration of UGT and OBBT and identification of the intrinsic predictors of virtual cart abandonment behavior. In addition, it is one of the early attempts to examine the dimensional impact of escapism on eCart abandonment.

The purpose of this paper is to introduce the new construct online shopper confusion and to identify online confusion causes and consequences.

Data obtained from a projective technique and a quantitative study were analyzed to identify online shopper confusion causes. Two experiments employing different stimulus materials tested the conceptualized consequences of online shopper confusion.

Confusing online store elements are classified into three online confusion causes. Data yielded from two experiments using fictitious and real shopping scenarios as stimulus material show that a confusing internet retail process leads to negative consumer reactions.

The resulting taxonomy of confusing online store elements offers guidance on the creation of non-confusing online shopping trips, and highlights the relevance of a non-confusing internet retail process. Online shopper confusion is linked to negative behavioral reactions. Consequently, this research offers an explanation for undesirable consumer reactions in internet retailing.

The findings provide practitioners with concrete insights into how the internet retail process confuses shoppers which help to assess the confusion potential of their existing online stores and consider confusion issues in the development of new online stores.

This research is the first to explore confusion during the internet retail process. The multi-method approach offers highly valid insights into the causes and consequences of online shopper confusion.

This paper aims to examine the unintended negative effect of incentivizing shoppers to make unplanned purchases through incentive reminders during shopping trips.

Two experimental studies with between-subject designs were conducted to examine the effect of incentive reminders and related factors on abandonment intention.

When the search for unplanned purchases needed to reach promotional threshold fails, shoppers’ propensity to abandon a transaction increases if they are reminded of an incentive during their shopping trip. When the size of the planned purchases is relatively larger than the incentivized unplanned purchases, abandonment propensity is higher in response to reward type incentives, whereas when the size of the planned purchases is relatively smaller than the incentivized unplanned purchases, abandonment propensity is higher in response to avoidance type incentives.

This research intersects and integrates several research domains, specifically transaction abandonment, promotional reactance, unplanned purchases and promotion framing.

Findings from this research help managers understand the possible negative consequences of incentive reminders and offer suggestions for decreasing shopper propensities to abandon transactions in response to incentive reminders aimed at increasing transaction sizes.

This is the first study to highlight (i) the possible effect of incentive reminders on transaction abandonment; (ii) the influence of the size of unplanned purchases and incentive types on abandonment; and (iii) the underlying roles of perceived value of planned purchases and fairness perceptions in abandonment.

The purpose of this study is to characterize consumers with high impulse buying tendency (IBT) by comparing them with low-IBT consumers in an online shopping context.

Data were collected through a postal survey to a random sample of Swedish citizens, resulting in 144 responses, which were analysed statistically..

Results indicate that high-IBT consumers, compared to those with low IBT, are on average younger, more likely to be female and more frequent online shoppers with higher levels of trust in the internet. However, they seem more likely than low-IBT consumers to abandon their online shopping carts before completing the purchase, often because of need uncertainty.

The findings can give retailers a better understanding of consumers with high IBT and thereby increase the possibility to target and communicate with them more effectively. This is an interesting opportunity as both multi-channel shopping and impulse buying behaviour is likely to become even more common in the future.

The study contributes to the understanding of impulsive consumers, as it addresses the role of situational and socio-demographic attributes of high-IBT consumers compared to low-IBT consumers. The differences in online purchases, intentions to buy fashion online, shopping cart abandonment and trust in the internet suggest that even if IBT is a relatively stable and general personal trait, the tendencies to act on buying impulses may be more context-specific.

Coupons, in the form of “promotion codes”, are now a mainstay of the online shopping experience, but online coupon redemption differs substantively from that in traditional retailing. Offline redemption of coupons is customer‐initiated while Internet shoppers are usually prompted to enter a code towards the conclusion of the checkout process. This prompting may influence shopper perceptions and behaviors such as shopping cart abandonment. Results showed strong negative effects on price fairness, satisfaction, and purchase completion in the code‐absent group and positive effects on fairness and satisfaction in the code‐present group. Presents implications for effective market segmentation through the use of online coupon codes.

This paper is designed to illustrate how clickstream data, collected from a B2B web site and then analyzed using web analytics software, can be used to evaluate and improve B2B web site performance. A number of issues in the application of clickstream data and web analytics software are to be identified and discussed.

A case study approach is used to present some of the technical issues in the field of web analytics and to demonstrate their value in B2B web site management. Three field experiments, focusing on incorporating ways to discourage shopping‐cart abandonment and the use of two different free‐shipping promotions, were used as the basic research method for collecting the data. Web traffic conversion funnels are used to conduct the analysis and present the findings.

The analysis of clickstream data using web analytics procedures serves as a useful tool in the enhancement of a B2B web site by investigating how visitors move through the web site conversion process and complete their purchase. Improved sales result from each of the three field experiments.

Researchers may use the paper as evidence that web analytics methods can be applied successfully in a B2B application for a technology‐oriented company.

The paper illustrates the use of clickstream data to measure the progression of web site visitors through the conversion process toward purchase.

Insight is provided into the usefulness of web analytics as a framework for performance measurement that is used to drive success for B2B web sites.

Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.

The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.

The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.

The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.

To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.