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Abstrak :
Pandemi virus covid-19 yang melanda seluruh negara di dunia termasuk Indonesia. Kebijakan pemerintah terhadap physical distancing dan menjaga protokol kesahatan membuat keterbatasan ruang gerak masyarakat melakukan aktivitas fisik di luar. Sebagai salah satu pilihan hiburan dirumah atau disela-sela waktu istirahat kerja masyarakat cenderung menggunakan layanan video streaming yaitu Netflix. Netflix melakukan kolaborasi dengan beberapa stakeholder Telco Operator yang ada di Indonesia seperti Telkomsel, XL Axiata, dan Indosat Ooredo. Telco Operator tersebut dalam menarik subscriber Netflix dengan memberikan perhatian khusus seperti memberikan paket akses streaming Netflix yang bervariasi. Memasuki tahun 2021 kebijakan pembatasan sosial mulai melonggar dan aktivitas sudah banyak diluar rumah. Bagaimana langkah atau strategi mendapatkan dan menarik pelanggan Netflix terutama di Indonesia melalui Telco Operator seperti Telkomsel, XL Axiata, dan Indosat Ooredo. Oleh karena itu, Penelitian ini menggunakan metode permodelan Porter 5 Forces dengan menganalisis Telco Operator dalam menarik subscriber layanan Netflix di Indonesia. Dengan pemetaan kompetisi persaingan yang sejenis, daya tawar pemasok dan peluang terhadap Telco Operator dalam menarik subscriber Netflix. Hasil dari analisis permodelan Porter 5 Forces Telco Operator dalam menarik subscriber Netflix dengan keunggulan kompetitif dari tekanan ancaman pendatang baru dan daya tawar pemasok, sebagai indikator strategi berupa pendekatan diferensiasi produk dan kebebasan Netflix dalam menentukan pemasok dan kolaborasi antara Netflix dengan Operator di Indonesia ......The coronavirus (COVID-19) pandemic began to infect several countries in the world, one of them Indonesia. The government of Indonesia implements on physical distancing to preventif coronavirus (COVID-19) and implementation health protocols. Refer to the policy has impact of activities outside such as prohibited gatherings and cause a crowd. Activities that are usually carried out outside are shifted to work form home. During work from home some people prefer to spend that time watching a Netflix streaming services, when their rest the time. During the coronavirus (COVID-19) pandemic, that Netflix streaming services is often used by the public so it becomes an opportunity to collaborate with Telco Operators in Indonesia such are PT. Telkomsel, PT. XL-Axiata and Indosat Ooredoo. Each of these operators trying to attracting subcsribers Netflix with special attention, such as providing various internet quota packages for Netflix streaming services. As time goes on in 2021, activities that are required work from home are slowly not being implemented and some activities are allowed to be carried out outside from home. What is the strategy in dealing with these conditions and how to attract Netflix Subscribers, especially in Indonesia, through Telco Operators such are PT. Telkomsel, PT. XL-Axiata, and Indosat Ooredoo. Therefore, this study uses the Porter’s 5 Forces method by analyzing Telco Operators in attracting Netflix subscribers in Indonesia. By mapping similar competition, suppliers bargaining power and opportunities for Telco Operators to attract Netflix subscribers. The results of this study use Porter’s 5 Forces Telco Operators to attracting Netflix subscribers with a competitive advantage from the pressure of threats of new entrants and similar competitors, as an indicator of the strategy in the form of a product differentiation approach, and as well as collaboration between Netflix and Telco Operators in Indonesia.

Abstrak :
Kejadian pandemi COVID-19 telah mengubah perilaku konsumen dalam hal konsumsi hiburan. Munculnya layanan Over-the-Top video streaming services (OTT) telah meningkatkan kenyamanan dalam akses konsumen terhadap hiburan berupa film dan serial. Hal ini menyebabkan munculnya persaingan dalam industri layanan OTT video streaming services, dan oleh karena itu perusahaan-perusahaan perlu memahami perilaku konsumen, faktor pendorong penggunaan, dan faktor pendorong rekomendasi untuk dapat bersaing. Penelitian ini menginvestigasi faktor-faktor yang mempengaruhi niat perilaku konsumen dalam menggunakan dan merekomendasikan OTT video streaming services. Variabel-variabel model UTAUT2, content availability, involvement & interest, personalization, dan attitude towards piracy dieksplorasi dalam penelitian ini. Penelitian ini menggunakan perangkat lunak SmartPLS 4 dan SPSS 26 untuk analisis data, di mana data dikumpulkan melalui distribusi kuesioner kepada 308 responden. Partial Least Squares-Structural Equation Modeling (PLS-SEM) digunakan sebagai metode analisis data oleh peneliti untuk memperoleh informasi mengenai hubungan antar konstruk. Hasil penelitian menunjukkan bahwa habit, involvement & interest, serta hedonic motivation secara signifikan berpengaruh positif terhadap behavioral intention. Namun, variabel seperti performance expectancy, effort expectancy, social influence, facilitating conditions, price value, dan content availability tidak berpengaruh signifikan terhadap behavioral intention. Personalization dan behavioral intention to use ditemukan berpengaruh positif terhadap consumers behavioral intention to recommend. Studi ini menyarankan implikasi bagi OTT video streaming services, badan regulator, dan pihak lainnya untuk meningkatkan kinerja terkait isu-isu yang relevan. ......The occurrence of COVID-19 pandemic has altered consumer behavior in terms of entertainment consumption. Emergence of Over-the-Top video streaming services (OTT) resulted in enhanced convenience in consumers’ access to motion picture entertainment. This led to the rise of competition within the industry of OTT video streaming services, and therefore the urgency for companies to gain knowledge on consumer behavior, drivers of use, and recommending drivers in order to compete. This research investigates the factors influencing consumers' behavioral intention to use and recommend OTT video streaming services. The UTAUT2 model variables, content availability, involvement and interest, personalization, and attitude towards piracy are examined. This research utilized SmartPLS 4 and SPSS 26 software for data analysis, in which the data were collected through questionnaire distribution to 308 respondents. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was the method of data analysis used by the researcher to access information about relationships between constructs. The findings reveal that habit, involvement & interest, and hedonic motivation positively significantly affect behavioral intention to use. However, variables like performance expectancy, effort expectancy, social influence, facilitating conditions, price value, and content availability do not significantly impact behavioral intention. Personalization and behavioral intention to use were found to positively influence behavioral intention to recommend. The study suggests implications for OTT video streaming services, regulatory bodies, and other parties to improve performance regarding relevant issues.