English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Apparently, two different fields might share common knowledge. Such shared knowledge might have better strategic priority for commercial enterprises working on applying solutions from one area to another domain. For instance, when using solutions from "artificial intelligence" (AI) to given "social media marketing" (SMM) programs, this shared-information might accelerate cross-functional cooperation to attain completive advantage &#x2014; an area of study that is mainly under-researched. In this context, the current study presents a sustainable design model to reveal the range of linkage options between AI and SMM from commercial prospects. Methodologically, the patent database related to AI and SMM is employed to generate topics independently, using the classic topic model, Latent Dirichlet allocation. Then, those topics are mutually paired through bibliographic coupling. The study&#x2019;s findings observed cross-concept networks; it reveals a range of concept pairs, and each pair is linked through a unique value of coupling strength. For instance, the top five AI-SMM pairs show the highest coupling value and offer the maximum commonality of previous work(s) in the following areas: [accurate advertising; automation of customer&#x2014;response]; [automation of payment transaction; accuracy of transactions; and automation of network database, storage. This study contributes to the literature in three ways. First, each bibliographic coupling-based association shows a unique association of shared knowledge &#x2014; an influence of common prior art(s). Second, using citation-based linkage auto-updates to add sustainable features. Third, taking the patents database reflects the concepts covering technological activities. In summary, the current study has a specific focus, but overall analysis can be applied to other unrelated fields, making it capable of meeting complex challenges through sustainable cooperation. Bringing automation in information sharing might open promising doors for cross-field communication, capable of completing complex challenges for smart cooperation for sustainable industry development.

Refining the Smart Linkage Across Two Fields: Artificial Intelligence and Social Media Marketing Using LDA and Bibliographic coupling (August 2023)