Search results

The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.

Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.

This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.

The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.

The purpose of this paper is to develop and test a method that can gradually find a sweet spot between user experience and visual intensity of website elements to maximise user conversion with minimal adverse effect.

In the first phase of the study, the authors develop the method. In the second stage, the authors test and evaluate the method via an empirical study; also, an experiment was conducted within web interface with the gradual intensity of visual elements.

The findings reveal that the negative response grows faster than conversion when the visual intensity of the web interface is increased. However, a saturation point, where there is coexistence between maximum conversion and minimum negative response, can be found.

The findings imply that efforts to attract user attention should be pursued with increased caution and that a gradual approach presented in this study helps in finding a site-specific sweet spot for a level of visual intensity by incrementally adjusting the elements of the interface and tracking the changes in user behaviour.

Web marketing and advertising professionals often face the dilemma of determining the optimal level of visual intensity of interface element. Excessive use of marketing component and attention-grabbing visual elements can lead to an inferior user experience and consequent user churn due to growing intrusiveness. At the same time, too little visual intensity can fail to steer users. The present study provides a gradual approach which aids in finding a balance between user experience and visual intensity, maximising user conversion and, thus, providing a practical solution for the problem.

As one of China’s most influential social platforms, Xiaohongshu is considered an underexploited market with significant user traffic. This study aims to build on existing scholarly work on social media marketing by conducting an empirical analysis of Xiaohongshu’s content to explore effective marketing strategies for children’s books.

This study uses qualitative content analysis to investigate the marketing practices for children’s books on Xiaohongshu. By systematically coding and interpreting data, the authors identified core marketing strategies and their interactions among publishers of children’s books on the platform.

Based on viral marketing and social proof theories, the analysis delineates practices and interrelations among three key marketing strategy components: content creation, traffic navigation and sales conversion on Xiaohongshu. From this analysis, a conceptual model titled “Continuous ‘Planting a Seed’ of Interest: Strategies for Marketing Children’s Books on Xiaohongshu” was developed.

This research not only corroborates the existing literature on the transformative power of social media in marketing but also extends it by providing a focused examination of how these principles apply to the promotion of children’s books on Xiaohongshu. It also provides practical insights for publishers looking to develop effective marketing strategies.

This case is about “Red”, a cross-border e-commerce platform developed from a community which was built to share overseas shopping experience. With sharp insights into the consumption behavior of urban white-collar women and riding on its community e-commerce advantage, “Red”, a cross-border e-commerce startup, pulled in three rounds of financing within just 16 months regardless of increasingly competitive market. On the other hand, well-established platforms such as T-mall International and Joybuy also stepped in, and their involvement will also speed up the industry integration and usher in a reshuffling period. Confronted with the “price war” started by those e-commerce giants, in what ways can “Red” adjust its shopping experience and after-sales services to enhance the brand value and sharpen its edge?

This paper aims to investigate how value drivers of internet medical business model affect value creation through a configurational approach. The internet medical business model (IMBM) is such a business model that integrates online and offline medical services with the driving force of internet technologies covering prediagnosis, in-diagnosis and postdiagnosis. The outbreak of COVID-19 and the support of national policies have boosted the development of internet health care. However, there are still many challenges in practice, such as the unclear innovation path, as well as difficulties in landing and profiting. Academic research has not yet provided sufficient theoretical insights. Therefore, to better explain and guide practice, it is urgent to clarify the innovation path and mechanism of value creation for IMBM.

Based on the sample of 58 internet medical firms in China, this paper adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore the configurational effects of IMBM’s value drivers on value creation.

Building on the business model canvas and the characteristics of internet health care, five value drivers of IMBM are identified, namely, functional value proposition, emotional value proposition, user involvement, resource capabilities and connection properties. And the five value drivers form three configurations, which are, respectively, labeled as resource-driven configuration, user-operated configuration and product-combined configuration. From the perspective of the integration of traditional and emerging theories, such as resource-based view, internet economics and value cocreation, each configuration leads to value creation and improves value results with different mechanisms behind it.

First, combined with the business model canvas and the characteristics of internet health care, this paper identifies five value drivers of IMBM, thus improving the relevant research on internet health care. Second, based on the configurational effects, this paper discusses the mechanism behind the configurational effects of IMBM’s value drivers on value creation, thus expanding relevant research on the value creation of business models. Third, applying fsQCA and combining the advantages of qualitative research and quantitative research, this paper adds to the configurations of IMBM’s value drivers that achieve high-value results.

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.

THE history of design in manufacture over the last two hundred and fifty years could almost be compressed into three words—integration, disintegration, reintegration—for that broadly has been the sequence of development from the days of handcraftsmanship, through the mechanization of the first industrial revolution, to the present age of swiftly changing technology. In the pre‐industrial era, integration between design and manufacture was complete since the designer and maker were one. In many cases, too, the maker was also the retailer or distributor, selling in his front room what he had made in his back room and knowing his customers as well as he knew himself.

The purpose of the study is to discover a model of knowledge conversion and knowledge transferring/sharing barriers in an entrepreneurial team (ET) working with innovative users at the early and fuzzy front end (FFE) stage of collaborative product design (Co-PD) process.

The exploratory research framework included sampling, data collection and data analysis, through sequential levels of categorizations, undertaken jointly with constant comparative analysis. The sample frame is the pool of ETs/startups from university business accelerators that carry out Co-PD at the FFE stage. The research survey is based on observations of the collaborative ETs activities, questionnaires and in-depth interviews with them. The research was conducted on individual and team levels when Co-PD process and ET activities were in progress.

This study identified specific set of concepts of knowledge conversion and transferring/sharing and their barriers that reflect specificity of Co-PD processes at the FFE stage in collaborative ETs. The discovered conversion process is represented by the socialization, externalization and internalization, three-mode knowledge conversion model. The significance of barriers and frequency of their occurrence were measured in knowledge transferring/sharing in collaborative ETs on individual and team levels.

This study shows novel insights into how knowledge transfers/shares and converts in the context of ET working with innovative users in Co-PD process at the FFE stage.

The City of Melbourne seeks to retrofit 1,200 CBD properties by 2020 as part of the strategy to become carbon neutral, whilst Amsterdam aims to cut CO₂ emissions 40 per cent by 2025. Oversupply in the Amsterdam office market makes conversion to residential use viable. In examining converted buildings in Amsterdam and the Melbourne CBD typical attributes of converted stock can be identified to target retrofit measures. This paper seeks to focus on these initiatives.

In Amsterdam five case studies were undertaken to reveal and define building attributes that explain the viability of these conversions. On the other hand, the Melbourne study was based on a database assembled containing all Melbourne CBD office building adaptations carried out between 1998 and 2008. The research analysed the conversion of office buildings and the scope for sustainable retrofit evaluating a limited number of attributes known to be important in adaptation.

The outcomes of this research showed similarities and differences in scope, which are relevant to all urban areas where adaptation of office buildings can mitigate the impacts of climate change and enhance a city for another generation of citizens and users.

The outcomes highlight the property attributes that explain conversion viability and that are most strongly associated with conversions. In addition the research identifies some sustainability measures that are possible with this type of stock.

The paper compares and contrasts qualitative data from a small sample of buildings in Amsterdam with quantitative data from a census of all change of use adaptations in Melbourne from 1998 to 2008. The contrasting approaches make it possible both to explain the driving forces of adaptations and to deliver statistical evidence of what is described in the case studies. Despite the differing approaches it is possible to compare and contrast the attributes of properties from both cities.