[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124949-en":3,"doc-seo-124949-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124949,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","The Role of Machine Learning Algorithms in Shaping the Hedonic Treadmill from the Perspective of Mental Accounting","Subscription-based video streaming services have reshaped entertainment consumption by giving users on-demand freedom to watch films anytime and anywhere. These services have become a major disruptor to traditional television, DVD production, and cinema, accelerating behavioral shifts intensified by the Covid-19 period. In accounting research, the phenomenon is framed as mental accounting, where consumers perceive streaming benefits outweighing costs or sacrifices. This study uses a qualitative interpretative approach to propose a conceptual model of how machine learning–driven recommendations and predictions create hedonic treadmill conditions, through compatibility, variability, originality, personalization, and flexibility.","Jurnal Akuntansi  \nVol. 14, No.2, June 2024  \nISSN 2303-0356 Hal. 155-163  \nTHE ROLE OF MACHINE LEARNING ALGORITHMS IN SHAPING THE HEDONIC TREADMILL FROM THE PERSPECTIVE OF MENTAL  \nACCOUNTING  \nBonnie Soeherman1)  \nUniversitas Surabaya 1)  \n\n| ARTICLE INFO |\n| --- |\n| Article history:\u003Cbr>Received:9 April th,2024\u003Cbr>Revised: June 24 th,2024\u003Cbr>Accepted: June 28th , 2024 |\n| Keywords:\u003Cbr>data analytics,\u003Cbr>algorithm,\u003Cbr>video streaming service,\u003Cbr>mental accounting,\u003Cbr>hedonic treadmill |\n\nCorrespondence:  \nBonnie Soeherman 1) Universitas Surabaya 1) [bonnie_s@staff.ubaya.ac.id](bonnie_s@staff.ubaya.ac.id)  \nABSTRACT  \nThe development of subscription-based video streaming services has transformed the way humans consume entertainment by granting users the freedom to watch any film, anytime, and anywhere. The presence of such services has become the biggest disruptor to conventional television stations, DVD producers, and even cinema services. Film consumption behaviors have undergone a shift triggered by the Covid- 19 pandemic. Individuals have become accustomed to enjoying films from the comfort of their homes or their familiar surroundings, rather than having to travel far or purchase and store DVD discs. The streaming service business has skyrocketed and amassed a large number of subscribers. This reality indicates a change in the consumer decision-making patterns for video streaming services. Streaming services are perceived to provide more advantages or benefits compared to cost or sacrifices. In accounting studies, this phenomenon is referred to as mental accounting. Thus far, there have been few scientific studies attempting to address the topic of mental accounting in the video streaming service industry, particularly in relation to framing strategies and the creation of hedonic treadmills built from machine learning algorithms. This research aims to explain how successful video streaming service businesses create hedonic treadmill conditions for their customers, binding them to addiction. This study employs a qualitative method with an interpretative approach to video streaming services to design a conceptual model of how video streaming service businesses' machine learning algorithms create hedonic treadmills for their customers. The research findings indicate that machine learning algorithms can play a role in creating hedonic treadmills through the creation of five relevant values: compatibility, variability, originality, personalization, and flexibility through  \nrecommendation and prediction systems.  \nHow To Cite (Apa Style):  \nSuherman, Bonniie. (2004) . The Role of Machine Learning Algorithms in Shaping the Hedonic Treadmill from the  Perspective of Mental Accounting. Jurnal akuntansi , 155-163. [https://doi.org/10.33369/jakuntansi.14.2.155-163](https://doi.org/10.33369/jakuntansi.14.2.155-163)   \nINTRODUCTION  \nThe service of video streaming or subscription video on demand (SVOD) seems to have become a new entertainment necessity for those who are well-established with their basic needs. Such innovation has even disrupted conventional television channel services and, to some extent, movie theaters. These services offer diverse content, flexibility in viewing time and medium, as well as personalization at more affordable prices compared to conventional methods (McKenzie et al., 2023); (Tengeh & Udoakpan, 2021) . The number of subscribers to these services continues to increase annually with the emergence of various SVOD or streaming video offerings such as Netflix, Disney+ Hotstar, Viu, Vidio, Prime, and Hulu. According to (Dean, 2024), the number of Netflix subscribers reached 260.28 million worldwide, with a revenue of $33.72 billion in 2023. What are the strengths of video streaming services and how do they build their strategies?  \nHumans always engage in analysis and calculation in their minds when faced with economic decision-making choices, including choosing their film-watching preferences. Whether consc","cbCaigFnIyI9iRwC","https://ap.wps.com/l/cbCaigFnIyI9iRwC","pdf",210684,1,9,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"What does the hedonic treadmill mean in mental accounting for video streaming users?\",\"answer\":\"It describes a tendency for emotional pleasure to return to a baseline, motivating repeated engagement with the platform, similar to the treadmill analogy.\"},{\"question\":\"How does this research explain the role of machine learning in shaping hedonic treadmills?\",\"answer\":\"It proposes that machine learning recommendation and prediction systems create hedonic treadmill conditions by generating compatibility, variability, originality, personalization, and flexibility for customers.\"},{\"question\":\"Why are subscription video streaming services considered a major disruptor to conventional entertainment options?\",\"answer\":\"They offer diverse content, flexible viewing time and medium, and personalization at more affordable prices, while enabling consumers to watch from home rather than travel or buy and store DVDs.\"}]","The Role of Machine Learning Algorithms in Shaping the Hedonic Treadmill from the Perspective of Mental Accounting | 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