Dynamic <scp>AI</scp> ‐Embedded Super App: A Design‐Based Process Innovation for Customer Engagement and Value Creation

ABSTRACT Academic In an era where mobile applications (apps) struggle for longevity amidst fluctuating download and deletion rates, the emergence of super apps marks a pivotal transformation. A super app is a mobile app‐based service aggregator platform that promises extensive value for customers and businesses. While early efforts like Apple's MobileMe and Google Buzz yielded mixed results, generative AI technology now positions super apps as a viable, all‐encompassing solution. This study explores the rise of the super app phenomenon and its potential to revolutionize mobile engagement and usage. Underpinned by the human‐centered design‐thinking approach, comprising desirability, feasibility, and viability elements, this study defines the super app as a multi‐dimensional phenomenon and further identifies the key elements needed to develop a successful super app. The study proposes critical factors and a process framework for the successful development and adoption of super apps. The findings reveal that users' market context (emerging vs. developed) and network co‐dependence act as important moderating factors influencing the process of super app adoption and customer engagement. The study advances the domain of innovation management and proposes a strategic matrix for managers to plan and align stakeholder engagement activities effectively. The study opens avenues for future research in engagement, value creation, and digital innovation. Managerial In today's crowded app market, most apps have short lives and uneven customer engagement. Super apps mark a shift by combining services such as payments, e‐commerce, and communication in a single platform. They use adaptive interfaces and personalized features to keep users active. With generative AI improving recommendations and support, super apps drive stronger engagement and deliver value to customers and businesses. This study conceptualizes super app as an AI‐embedded, multi‐dimensional phenomenon grounded in human‐centered design thinking, emphasizing the critical role of elements of desirability, feasibility, and viability. It identifies various key customer‐level, firm‐level, and context‐level elements for building successful super apps. Findings emphasize that the adoption of super apps and customer engagement vary across markets (emerging vs. developed economies) and are based on the degree of network co‐dependence. To support implementation, the study introduces a 2 × 3 strategic matrix that links market penetration levels (high, moderate, low) with stakeholder engagement (customers and participating firms). Suggested strategies include sustenance (e.g., AI‐powered loyalty programs), growth (flexible revenue‐sharing models), and acquisition (service bundling and innovation). Finally, while metadata collection enables sharper insights, managers must ensure strong data privacy, encryption, and monitoring to protect trust for sustaining long‐term customer and ecosystem relationships.

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Publication Details

Journal
Journal of Product Innovation Management
Published
2025-09-25
DOI
https://doi.org/10.1111/jpim.70009
Citations
1
Primary Topic
Service and Product Innovation
Type
article
Field-Weighted Citation Impact
2.07
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article

Dynamic AI ‐Embedded Super App: A Design‐Based Process Innovation for Customer Engagement and Value Creation

Shaphali Gupta, Soniya Gupta‐Rawal, Pooja Shrivastava
1 citations
Journal of Product Innovation Management
Service and Product Innovation
2.07
article

Dynamic AI ‐Embedded Super App: A Design‐Based Process Innovation for Customer Engagement and Value Creation

Shaphali Gupta, Soniya Gupta‐Rawal, Pooja Shrivastava
article en
1 citations

Abstract

ABSTRACT Academic In an era where mobile applications (apps) struggle for longevity amidst fluctuating download and deletion rates, the emergence of super apps marks a pivotal transformation. A super app is a mobile app‐based service aggregator platform that promises extensive value for customers and businesses. While early efforts like Apple's MobileMe and Google Buzz yielded mixed results, generative AI technology now positions super apps as a viable, all‐encompassing solution. This study explores the rise of the super app phenomenon and its potential to revolutionize mobile engagement and usage. Underpinned by the human‐centered design‐thinking approach, comprising desirability, feasibility, and viability elements, this study defines the super app as a multi‐dimensional phenomenon and further identifies the key elements needed to develop a successful super app. The study proposes critical factors and a process framework for the successful development and adoption of super apps. The findings reveal that users' market context (emerging vs. developed) and network co‐dependence act as important moderating factors influencing the process of super app adoption and customer engagement. The study advances the domain of innovation management and proposes a strategic matrix for managers to plan and align stakeholder engagement activities effectively. The study opens avenues for future research in engagement, value creation, and digital innovation. Managerial In today's crowded app market, most apps have short lives and uneven customer engagement. Super apps mark a shift by combining services such as payments, e‐commerce, and communication in a single platform. They use adaptive interfaces and personalized features to keep users active. With generative AI improving recommendations and support, super apps drive stronger engagement and deliver value to customers and businesses. This study conceptualizes super app as an AI‐embedded, multi‐dimensional phenomenon grounded in human‐centered design thinking, emphasizing the critical role of elements of desirability, feasibility, and viability. It identifies various key customer‐level, firm‐level, and context‐level elements for building successful super apps. Findings emphasize that the adoption of super apps and customer engagement vary across markets (emerging vs. developed economies) and are based on the degree of network co‐dependence. To support implementation, the study introduces a 2 × 3 strategic matrix that links market penetration levels (high, moderate, low) with stakeholder engagement (customers and participating firms). Suggested strategies include sustenance (e.g., AI‐powered loyalty programs), growth (flexible revenue‐sharing models), and acquisition (service bundling and innovation). Finally, while metadata collection enables sharper insights, managers must ensure strong data privacy, encryption, and monitoring to protect trust for sustaining long‐term customer and ecosystem relationships.

Journal of Product Innovation ManagementVol. 43(1)
Indian Institute of Management Kozhikode (IN), University of Cambridge (GB), Data Management (Italy) (IT)
Openalex Percentile: Top 10%
Service and Product Innovation
2.07
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