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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.

Under emerging social media technology, mobile learners' behavior analysis and legality education have important practical significance. The research aims to detect the mobile learning (M-learning) learners' behavior in legality education under the background of the Internet era and improve the learning and teaching effect of online legality education and law popularization.

This paper proposes a model based on deep learning (DL) fuzzy clustering analysis (FCA), and bidirectional encoder and decoder (ENDEC) of converter model to detect the mobile learners' behaviors in online legality education under the current social media. Then, the effectiveness of the proposed model is tested. The proposed model expects to be applied to multimedia teaching and law popularization activities and provides some theoretical reference and practical value for improving the effectiveness of online teaching.

The experimental results show that in the learner behavior detection process of M-learning-oriented online legality education, the model's accuracy can reach 99.8%. The response time is shorter than other algorithms. Overall, the application effect of the proposed model and algorithm is good and can be applied in practice.

The research results may lack universality due to the selected research methods. Therefore, researchers are encouraged to test the proposed methods further. In the future, it is necessary to expand the type and scale of text data to improve the accuracy of data detection.

The research results provide a specific theoretical reference and practical significance for improving the learning effect of online M-learning-oriented legality education.

This paper meets the needs of mobile learner behavior analysis based on social media.

After reading and discussing the case, the participants would be able to:▪ articulate the challenges associated with retailing of organic products.▪ suggest paid, owned and earned digital marketing tools to Manav Chetna Vikas Kendra (MCVK);▪ suggest a digital marketing budget;▪ discuss essential elements of a good website design; and▪ discuss various website analytics metrics.

This case describes the challenges faced by the founder, Ajay Dayama, and members of MCVK, who believed in the concept of sustainable community living through the production and marketing of organic food products. They believed that they would be able to share their philosophy of sustainable living through their products reaching out to a larger population rather than just being consumed by community members. This paved the way for the creation of a brand by the name SATT offering products under the lifestyle, nutriment and wellness categories. Marketing and sales of SATT products came with a bundle of challenges, and it was not easy to convince customers about the authenticity, quality and pricing of these products. Many organic products sold by competitors were available on e-commerce platforms, while SATT relied on direct marketing. Low customer acceptance for SATT products would weaken the sustainability dream of the community. How MCVK could increase awareness and acceptance of SATT products was a big area of concern for Ajay.

This case is suitable for students enrolled for full credit course on Digital Marketing at postgraduate level. The case can be discussed towards the middle of the course.

Teaching Notes are available for educators only.

CSS 8: Marketing.

The paper aims to present a framework for integrating the concepts of business continuity and business resilience with the aim of developing a concept of always-on business.

Literature review, conceptual and case-based.

A conceptual model for integrated “always-on business” solution based on continuous comouting technologies, business continuity, disaster recovery, IT/business resilience and several organational frameworks.

Presented framework can be used for integrating business continuity and business resilience in modern digital age; and transforming business systems into “always-on business”.

The study aims to investigate the time for social media posts and reviews in order to determine the best timing to ensure maximum outreach and interactions from users. The study intends to analytically investigate a company's Facebook and Instagram pages to get meaningful insights for effective post management.

“Great Deal Tires” company’s Facebook and Instagram business pages were taken as the case study and patterns and analytical insights for different posts using Facebook and Instagram analytics were identified. The study categorically selected posts from Facebook pages and Instagram pages that were posted at different times and assessed on their impact.

According to the study, Tuesday and Wednesday have higher engagement on the Great Deal Tires Facebook page, while Friday has higher engagement on Instagram. The study also provided valuable insights into post content and timing in order to increase the marketing impact of the posts.

The study provides an analytical framework for analyzing post and review timing on various company business pages, allowing marketers to initiate more user visits and interactions.

The use of brand slogans that represent brand concepts on app launch pages can improve user brand impressions. The purpose of this paper is to investigate the impact of using animated or static spokes-characters with brand slogans on app launch pages.

Using the theory of attention selection, the authors conducted two experiments to study the boundary and mediation path of the influence of the motion attributes of spokes-characters (static vs animated) on brand memory based on app launch time (3 s vs 5 s), user engagement with spokes-characters and the level of attention to brand slogans.

Study 1 explores the effect of the interaction between launch time and the motion attributes of spokes-characters on brand memory. The results show that when the launch time of the app is 3 s, the advertisement memory effect of using a static spokes-character is better than that of using an animated spokes-character; when the launch time of the app is 5 s, the advertisement memory effect of using an animated spokes-character is better than that of using a static spokes-character. Study 2 shows that user engagement with spokes-characters and the level of attention given to brand slogans play a continuous mediating role in the effect of the interaction between launch time and the motion attributes of spokes-characters on brand memory.

This paper contributes to the marketing literature by expanding the knowledge of spokes-characters and animated visual images, providing new insights for future research.

This study aims to develop a taxonomy of requirements for mobile BIM technologies (MBT), clarify the relating terms and concepts, and identify the interactions between MBT features and the construction management functions on sites.

A positivist approach with elements of interpretivism is adopted to allow to capture what is perceived as “reality” in relation to individuals’ interpretation and experience in the use and implementation of MBT. This is achieved by using a mixed qualitative-quantitative approach that can capture the various understandings of MBT. The research methods included a longitudinal case study over 12 months, two project workshops, expert interviews and an industry survey that together helped to investigate MBT at project, enterprise and industry levels.

The MBT requirements taxonomy included requirements relating to both project and organisation. Project requirements addressed MBT functionalities for sites and information management, while organisation requirements focused on the integration of MBT solutions with the enterprise from information technology, legal and security perspectives. A detailed matrix showing the interactions between five key MBT features and seven construction management functions was also developed.

The two constructs developed by this study can help researchers to structure their investigation of key uses of MBT applications and their benefits. It can be used by researchers aiming to investigate integrated approaches to the digitalisation of construction sites, such as those enabled by Digital Twins. The interaction matrix can aid researchers in evaluating the intersections between the MBT functionalities and the site construction management functions (e.g. theoretical analysis of interactions from Lean Construction, benefit evaluation perspective). More broadly, the two constructs can support research and practice investigating the development of data-driven approaches on construction sites.

The developed MBT taxonomy can guide construction organisations in selecting suitable MBT for Field BIM for their projects. It can also act as a baseline against which varying MBT solutions can be compared.

Constructs such as taxonomies for MBTs; an understanding of MBT capabilities and use within the industry; and a lack of delineation between related terms, such as Mobile BIM, Field BIM, Site BIM, Cloud BIM and Mobile Apps, were lacking in the literature. This study contributed to addressing this gap.

Based on a lexical analysis of publications on 529 Facebook pages, published between 2013 and 2017, this research explores how Brazilian left-wing activist groups participate on Facebook to coordinate their opposition and engage in social struggles. This chapter shows how activist groups set up two main digital network repertoires of action when mobilizing on Facebook. First, in direct connection with major political events, the platform is used as a media arena to challenge governments’ political actions and second, it is employed as a tool to coordinate mobilization, whether these mobilizations are demonstrations on the street or at cultural events, such as at a music concert. These repertoires of action exemplify ways in which contemporary Brazilian activism is carried out at the intersection of online and offline engagements. While participants engage through these two repertoires, this network of activists is held together over time through a more mundane type of event, pertaining to the repertoire of action allowing the organization of mobilization. Stepping aside from opposition and struggles brought to the streets, the organization of cultural activities, such as concerts and exhibitions, punctuates the everyday exchanges in activists’ communications. Talk about cultural events and their related social agendas structures activist networks on a medium-term basis and creates the conditions for the coordination of (future) social movements, in that they offer the opportunities to stay in contact, in addition to taking part in occasional gatherings, between more highly visible social protests.

The purpose of the current study is to examine a social network site (SNS) users' overall satisfaction with SNS use in conjunction with their fan page visiting activities. We examined overall satisfaction with SNS usage from the lens of people's perceptions acquired from the use of sub-components of SNS.

The current study employed uncertainty reduction theory (URT) and general systems theory (GST) to examine antecedents affecting overall satisfaction with SNS use. Five constructs were adopted: interactive and passive uncertainty reduction strategies, perceived usefulness and continuance visiting behavior, satisfaction, and perceived functional benefits. Using a web-based survey, we analyzed 200 SNS users who follow at least one company's fan page, utilizing seemingly unrelated regression models to test hypotheses empirically.

Research findings reveal that uncertainty reduction strategies supported by URT are significantly associated with the perceived usefulness of a company's fan page. In turn, we found that perceived usefulness becomes a strong motivator to continuance visits to the fan page. The frequency of return visiting behaviors eventually accounts for overall satisfaction with SNS. Perceived functional benefits moderates the relationship between perceived usefulness and visiting behaviors significantly.

The current study contributes to information systems (IS), electronic communication, and their adjacent academic disciplines in providing evidence, including (1) the impact of uncertainty reduction strategies on continuance visiting behaviors in the SNS context, (2) SNS functionalities influencing the relationship between people's belief and behavior, and (3) theoretical significant perceptional link between a sub-component and a whole.

This study aims to explore the evidence-based usage patterns of higher education commission (HEC) subscribed e-journal databases in the university digital library used by the scholarly community and the academics’ online searching behaviour at a higher education institution in Pakistan.

The study used an explanatory sequential mixed methods approach. Raw transaction log data were collected for quantitative analysis, and the interview technique was used for qualitative data collection and thematic analysis.

Log analysis revealed that HEC subscribed databases were used significantly, and among those, scholarly databases covering various subjects were more frequently used than subject-specific society-based databases. Furthermore, the users frequently accessed the needed e-journal articles through search engines like Google and Google Scholar, considering them sources of free material instead of the HEC subscribed databases.

It provides practical implications for examining the evidence-based use patterns of e-journal databases. It suggests the need for improving the access management of HEC databases, keeping in view the usage statistics and the demands of the scholars. The study may also help create market venues for the publishers of scholarly databases by offering attractive and economical packages for researchers of various disciplines in developing and underdeveloped countries. The study results also guide the information professionals to arrange orientation and information literacy programs to improve the searching behaviour of their less frequent users and enhance the utilization of these subscribed databases.

The study is part of a PhD project and, to the best of the authors’ knowledge, is the first such work in the context of a developing country like Pakistan.