Effects of cognitive absorption on continuous use intention of AI-driven recommender systems in e-commerce

Acharya, Nirmal Kumar; Sassenberg, Anne-Marie; Soar, Jeffrey

doi:10.1108/fs-10-2021-0200

Cited by 12 publications

(10 citation statements)

References 51 publications

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“…The use of cutting-edge algorithms like CNN and CF diversifies sentiment analysis [38,61]. Ensemble classifiers like Random Forest [40,48] and hybrid systems like CNN-LSTM architectures [46,101,114] demonstrate purposeful integration of several techniques for sentiment analysis. Researchers believe this technological transition is a purposeful move from conventional methodologies to advanced integration of cutting-edge technology, notably in NLP and machine learning.…”

Section: Discussionmentioning

confidence: 99%

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Malik,

Bilal

2024

Preprint

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In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

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Section: Discussionmentioning

confidence: 99%

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Malik,

Bilal

2024

Preprint

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“…This research adds significant contributions to the literature by empirically determining different influences of cognitive absorption and perceived usefulness on shoppers' intentions to reuse RSs. There has been little research on the impact of holistic consumer experience on behavioural intentions to reuse recommender systems [49], resulting in a lack of consensus, especially regarding the direct impact of the holistic consumer experience on behavioural intentions to reuse RSs. This research shows that a user's holistic experience, as measured by cognitive absorption, has a strong direct influence on behavioural intentions in the context of recommender systems.…”

Section: Discussionmentioning

confidence: 99%

“…Cognitive absorption in information technology refers to an individual's holistic experience and complete involvement with information technology [39,43,48,49]. It was initially seen as a trait but is now considered both a trait and a state [50].…”

Section: Cognitive Absorptionmentioning

confidence: 99%

“…Cognitive absorption stems from the absorption characteristic and is a condition of profound involvement with information technology [51,52]. Cognitive absorption has been primarily used in information systems literature to study the formation of a user's intentions to use new technologies [23,49]. Key studies on cognitive absorption in IS are listed in Table 1.…”

Section: Cognitive Absorptionmentioning

confidence: 99%

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The Role of Cognitive Absorption in Recommender System Reuse

2023

Self Cite

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E-commerce is the trade of services and goods via electronic means such as the Internet. It is critical in today’s business and user experience. Most current e-commerce websites employ various technologies such as recommender systems to provide customers with personalised recommendations. Taking this as a cue, this study investigates the effect of cognitive absorption to estimate the holistic experience of recommender systems on shoppers’ intentions to reuse recommender systems. Data collected from 366 online shoppers were analysed using structural equation modelling to test the proposed hypotheses. The findings highlight that cognitive absorption directly and indirectly affects shoppers’ behavioural intentions to reuse recommender systems. The results also exposed the moderating effect of gender on shoppers’ behavioural intentions to reuse recommender systems. An importance-performance map analysis was also conducted to identify significant areas of improvement for e-vendors. This study contributes to advancing existing knowledge relevant to shoppers’ behavioural intentions to reuse recommender systems. The study also provides e-vendor managers with insights into online shoppers’ decision making.

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“…Saade et al [47] considered temporal dissociation, focused immersion, and heightened important enjoyment aspects of determining the individual intention to use online learning systems. Acharya et al [23] observed the direct effect of focused immersion and curiosity of continued intention to use. However, they observed no relationship between temporal dissociation and intention to use.…”

Section: Hypotheses 5a-cmentioning

confidence: 99%

Designing for curiosity enhances absorption and continued intention to use MOOCs

Faisal,

Younas,

De Andrés

et al. 2023

Preprint

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Rapid technological growth and frequent modification in user usage behavior consequently emerge new challenges for online learning service providers to continuously determine individuals’ experiences to maintain their level of engagement. Accessible interfaces and interactive services play a key role in increasing user engagement with technologies. The intent is to seek deeper insights to determine potential interface design features that heighten curiosity and absorption, leading to continued intention to use. An application MOOC prototype was created to collect data from participants and used to validate the proposed research model and hypotheses. The partial least squares method was used to analyze the collected data. It was found that the design characteristics increased the level of curiosity and immersed participants in the learning environment, causing them to lose their sense of time and develop a sense of temporal dissociation. This study will draw the attention of e-learning service providers to learners' perceptions of learning resources.

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Effects of cognitive absorption on continuous use intention of AI-driven recommender systems in e-commerce

Cited by 12 publications

References 51 publications

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

The Role of Cognitive Absorption in Recommender System Reuse

Designing for curiosity enhances absorption and continued intention to use MOOCs

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