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Understanding the role of gamification and loyalty programs in restaurant apps: a systematic literature review and conceptual framework development Sutrisno, Julius; Tarigan, Aritha; Purnomo, Ivanna Dominique Celesta
Journal of Business & Applied Management Vol 19, No 1 (2026): Journal of Business & Applied Management
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/jbam.v19i1.9775

Abstract

The rapid digital transformation in the restaurant industry has led to the widespread adoption of mobile applications incorporating gamification, rewards, and loyalty programs to enhance customer engagement and retention. This study conducts a systematic literature review to synthesize recent research on these strategies in restaurant mobile apps. Following the PRISMA guidelines, a comprehensive search of the Scopus database identified 587 records, with 42 studies published between 2020 and 2026 meeting the inclusion criteria. Thematic analysis revealed four primary themes: (1) mechanisms of user engagement driven by motivational affordances fulfilling autonomy, competence, and relatedness needs; (2) architecture of rewards and loyalty programs evolving from transactional to digital, tiered, and personalized ecosystems; (3) outcomes on customer loyalty encompassing both attitudinal and behavioral dimensions; and (4) challenges including privacy concerns, poor design, and wellbeing implications. The findings are interpreted through Self-Determination Theory, Service-Dominant Logic, and Oliver's loyalty framework, demonstrating that gamification enhances customer experience and fosters loyalty through need satisfaction and value co-creation. Practical implications guide restaurant managers and app developers in designing layered gamification experiences, navigating personalization-privacy trade-offs, and implementing ethical engagement practices. The review identifies critical research gaps, including the need for longitudinal studies, cross-cultural comparisons, and investigations of negative outcomes. This synthesis contributes to theoretical development in digital loyalty and offers actionable insights for industry practitioners.
Mapping the Evolution of AI Chatbots in Indonesia (2021-2025): A PRISMA-Based Systematic Literature Review on Applications, Technologies, and Impacts Antonius Felix; Arta Moro Sundjaja; Julius Sutrisno; Nanang Suryadi
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 8 No. 1 (2026): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v8i1.14942

Abstract

The rapid development of artificial intelligence has accelerated the adoption of chatbots in organizations in Indonesia. But there is no systematic synthesis of the development of this technology in Indonesian context. This research provides a systematic review of the development and implementation of AI chatbots in Indonesia in 2021–2025, with the aim of filling the research gap related to sectoral applications, technological trajectories, and contextual challenges. A systematic literature review was conducted following the PRISMA 2020 guidelines on the Scopus, Google Scholar and arXiv databases to collect 257 initial records. After duplicate removal and a multi-step screening process, 16 high-quality studies were included in the final synthesis. Thematic analysis identified four main findings: (1) AI Chatbots are found in higher education, healthcare, banking, public services, fintech, e-commerce, and SMEs; (2) The technology has evolved from rule-based approaches (AIML, TF-IDF) to machine learning (Seq2Seq LSTM, Rasa+IndoBERT) and the latest large language model integration (GPT-3.5, Vertex AI); (3) Reported impacts include improved user satisfaction (SUS scores 80.1), operational efficiency, and 24/7 service availability; and (4) Existing challenges include accuracy in Indonesian language processing, complexities in system integration, data privacy issues, and varied levels of digital literacy. This review is the first systematic mapping of Indonesia’s AI chatbot landscape and makes evidence-based recommendations for the development of locally-adapted, culturally-sensitive models. Results show that future chatbot development should emphasize Indonesian language datasets and hybrid architectures that combine automation and human oversight.