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"Perkembangan ekonomi digital di Indonesia semakin berkembang pesat. Jumlah pengguna Electronic Commerce (e-commerce) di Indonesia juga diproyeksikan meningkat terus menerus. Terdapat berbagai alasan pendorong customer berbelanja di e-commerce. Ulasan online konsumen mempunyai pengaruh yang cukup signifikan terhadap perilaku pembelian konsumen dan telah menjadi sumber informasi penting bagi konsumen, memengaruhi sekitar 20–50% keputusan pembelian online. Kondisi saat ini, E-commerce XYZ belum melakukan research atau investigasi lebih lanjut terkait faktor-faktor apa saja yang dapat membuat customer memberikan ulasan. Tujuan dari penelitian adalah untuk menganalisis beberapa faktor yang memengaruhi niat pelanggan memberikan ulasan online / electronic word of mouth (EWOM). Penelitian ini diharapkan dapat menjadi pembelajaran untuk meningkatkan product review rate, yang erat kaitannya dengan kepuasan pelanggan dan akan berpengaruh terhadap kenaikan add to cart rate. Penelitian dilakukan dengan metode campuran, yaitu secara kuantitatif dengan menyebarkan kuesioner dan secara kualitatif dengan melakukan wawancara. Dalam penelitian ini, beberapa kerangka model yang dipilih berdasarkan analisis faktor dan adopsi dari studi-studi sebelumnya yaitu model kesuksesan sistem informasi dari DeLone &McLean yang mengintegrasikan teori kualitas e-service, serta teori determinasi diri dan social influence yang diadopsi dari teori UTAUT.Kuesioner disebar secara online melalui google form. Pengolahan analisis statistik yang digunakan adalah Partial Least Square (PLS) dengan tools SmartPLS v.4. Hasil dari penelitian memberikan kesimpulan bahwa e-service quality, attitude & customer satisfaction memengaruhi niat pelanggan memberikan ulasan online secara positif. Hipotesis bahwa delivery condition memengaruhi e-service quality secara positif, ditolak. Kemudian dilakukan wawancara dan analisis tematik untuk eksplorasi masalah dan pemberian rekomendasi yang difokuskan kepada hasil hipotesis yang diterima.

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The digital economy in Indonesia is growing rapidly. The number of Electronic Commerce (e-commerce) users in Indonesia is also projected to continuously increase. There are various motivating reasons for customers to shop on e-commerce platforms. Online consumer reviews have a significant influence on consumer buying behavior and have become a crucial source of information for consumers, affecting about 20–50% of online purchase decisions. Currently, E-commerce XYZ has not conducted further research or investigation into the factors that can prompt customers to leave reviews. The purpose of this study is to analyze several factors that influence customers' intentions to provide online reviews, or electronic word of mouth (EWOM). This research is expected to provide insights to enhance the product review rate, which is closely related to customer satisfaction and is likely to impact the increase in the add-to-cart rate. The research was conducted using mixed methods, namely quantitatively by distributing online questionnaires and qualitatively by conducting interviews. In this study, selected frameworks are based on factor analysis and adoption from previous studies, including the DeLone & McLean information system success model that integrates the theory of e-service quality, as well as self-determination theory and social influence adopted from the UTAUT theory.

Questionnaires were distributed online via Google Forms. The statistical analysis method used is Partial Least Square (PLS) with SmartPLS v.4 tools. The findings of the study conclude that e-service quality, attitude, and customer satisfaction positively influence the customers' intention to provide online reviews. The hypothesis that delivery condition positively affects e-service quality was rejected. Subsequently, interviews and thematic analysis were conducted to explore issues and provide recommendations focused on the accepted hypothesis results."

"Pemanfaatan data untuk menghasilkan informasi yang dapat mendukung pengambilan keputusan bisnis semakin banyak diaplikasikan oleh berbagai perusahaan. Salah satu data yang dimanfaatkan dalam pengambilan keputusan tersebut adalah data pelanggan mengingat perannya dalam mengetahui perilaku pelanggan. Salah satu perusahaan yang memanfaatkan data pelanggan dalam pengambilan keputusan bisnis adalah English First (EF). Dalam membantu menetapkan strategi bisnis untuk meningkatkan perfoma penjualan, perusahaan menghadapi kendala penurunan performa penjualan perusahaan yang disebabkan oleh buruknya kualitas data pelanggan, sehingga strategi bisnis yang dihasilkan kurang tepat. Perusahaan berfokus kepada beberapa dimensi kualitas data pelanggan di perusahaan yaitu completeness, accuracy, dan consistency. Strategi untuk manajemen peningkatan kualitas data pada perusahaan perlu disusun guna penyusunan strategi bisnis yang tepat dan dapat meningkatkan performa penjualan. Penyusunan strategi manajemen peningkatan kualitas data dilakukan dengan melakukan penilaian terhadap dimensi-dimensi kualitas data untuk mengidentifikasi kondisi kualitas data saat ini di perusahaan EF. Selain itu, identifikasi kondisi manajemen dan praktek kualitas data di perusahaan saat ini juga dilakukan untuk dapat mengetahui kesenjangan antara kondisi perusahaan saat ini dengan kondisi yang diharapkan oleh perusahaan. Strategi peningkatan kualitas data yang dihasilkan dari analisis kesenjangan kondisi kualitas data dan manajemen & praktek kualitas data terdiri dari 8 (delapan) domain manajemen kualitas data. Delapan domain tersebut yaitu harapan dari kualitas data, penggunaan dimensi dari kualitas data, kebijakan data, prosedur, tata kelola data, standarisasi data, teknologi, dan pengelolaan kerja. Hasil dari strategi tersebut disusun menjadi rekomendasi solusi dan diurutkan berdasarkan prioritas dengan balance scorecard. Strategi yang memperoleh prioritas tinggi yaitu standardiasi aktifitas dan isu kualitas data serta mengidentifikasi ekspektasi dari kualitas data pada setiap dimensi kualitas data.

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Data utilization to generate insights to support business decision making has been implemented in many companies. One of the most utilized data is customer data as it could provide information regarding customer’s behavior. One of the companies that utilize customer data is English First (EF). EF is a company in education sector and have more than 20 years of experience in Indonesia. EF utilize customer data in Customer Relationship Management system to produce a business strategy to boost company performance. However, since data in Customer Relationship Management system is stored by human, it has a low quality and resulted in a mismatch business strategy. Strategy to improve data quality management in the company needs to be produced in order to generate a precise business strategy and could boost company sales performance. Data quality assessment towards data quality dimensions needs to be done to produce a improve data quality management strategy. The assessment is needed to identify current data quality condition in EF. Other than that, identification of data quality management and practices in the company are needed to identify as-is management & practices in the company, company’s data quality expectation, and identify the gap between best practice & current condition. The result of data quality improvement strategy consists of 8 (eight) data quality management domains. Those domains are data quality expectation, data quality management, data quality, data policy, data procedure, data governance, data standardization, technology, and work management. The end result is a solution recommendation to improve data quality in EF and sorted by priority with the help of balance scorecard. The strategies that have high priority are company needs to standardized data quality activities and issues in the company as well as identify business expectation of each data quality dimension."

"Pandemi COVID-19 menjadi tantangan besar bagi perekonomian global. Berbagai sektor mengalami kontraksi negatif pertumbuhan. Berbeda dengan sektor telekomunikasi yang mengalami peningkatan permintaan jaringan komunikasi dan internet yang menghasilkan kompetisi dalam memberikan pelayanan terbaik dan menjaga kepuasan pelanggannya. Termasuk PT Telekomunikasi Indonesia yang merupakan leading company industri telekomunikasi. Laporan Customer Experience Satisfaction Measurement menunjukkan perusahaan belum dapat mencapai target dalam pengelolaan kepuasan pelanggan yang diukur menggunakan Net Promoter Score (NPS), khususnya pada layanan wholesale network connectivity. Penelitian ini melakukan evaluasi terhadap model bisnis aktual perusahaan untuk peningkatan customer experience (CX) dengan melakukan transformasi digital di seluruh elemen model bisnis melalui proses wawancara kepada tiga narasumber yang berasal dari Direktorat Wholesale and Internasional Services yang bertanggung jawab dalam perumusan strategi dan kebijakan bisnis wholesale. Evaluasi model bisnis dilakukan dengan menggunakan business model canvas. Manfaat penelitian ini adalah dirumuskannya model bisnis digital baru bagi perusahaan khususnya segment wholesale yang mendukung dalam peningkatan customer experience layanan wholesale network connectivity. Evaluasi model bisnis divalidasi oleh Direktorat Wholesale and Internasional Services. Upaya peningkatan CX dilakukan melalui penyederhanaan proses-proses internal perusahaan, penawaran produk/layanan baru, kemudahan dalam delivery layanan, serta peningkatan fokus utama pada penggalian kebutuhan pelanggan. Usulan tersebut dapat dimanfaatkan perusahaan sebagai referensi dalam menyusun strategi transformasi layanan wholesale network connectivity.

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The COVID-19 pandemic is a major challenge for the global economy. Various sectors experienced a negative contraction in growth. In contrast to the telecommunications sector, which experienced an increase in demand for communication networks and the internet which resulting in making competition to provide the best service and maintain customer satisfaction. Including PT Telekomunikasi Indonesia which is a leading company in the telecommunications industry. The Customer Experience (CX) Satisfaction Measurement report shows the company has not been able to achieve the target in managing customer satisfaction as measured using the Net Promoter Score, especially in wholesale network connectivity services. This study evaluates the company's actual business model to improve customer experience by carrying out digital transformation in all elements of the business model through an interview process to three sources from the Wholesale and International Services Directorate who are responsible for formulating wholesale business strategies and policies. The evaluation of the business model is carried out using the business model canvas. The benefit of this research is the formulation of a new digital business model for the company, especially the wholesale segment that supports the improvement of customer experience for wholesale network connectivity services. The evaluation of the business model was validated by the Wholesale and International Services Directorate. Efforts to improve CX are carried out through simplifying the company's internal processes, offering new products/services, facilitating service delivery, and increasing the main focus on exploring customer needs. The company can use this proposal as a reference in formulating a wholesale network connectivity service transformation strategy."

"Salah satu tantangan yang dihadapi industri akomodasi di Indonesia adalah sulitnya melakukan pengambilan keputusan berdasarkan data dan informasi yang dapat diandalkan. Saat ini, Indonesia belum memiliki data usaha pariwisata yang komprehensif dan belum ada pusat informasi kepariwisataan berskala nasional yang dapat digunakan oleh para pemangku kepentingan. Untuk memperoleh data, mayoritas pengelola akomodasi masih melakukan praktik information sharing secara manual dan belum menggunakan sistem terintegrasi. Penelitian ini bertujuan untuk mengembangkan arsitektur dan prototipe (front-end) sistem business intelligence (BI) berbasis information sharing untuk mendukung proses revenue management di industri akomodasi di Indonesia. Pendekatan penelitian yang digunakan adalah Design Science Research yang menghasilkan solusi sesuai kebutuhan pemangku kepentingan di sektor akomodasi. Kajian pustaka dilakukan dengan metode Systematic Literature Review. Pengolahan dan analisis data wawancara menggunakan metode thematic analysis. Pengumpulan data pada penelitian ini dilakukan melalui observasi data pariwisata, observasi data pada online travel agent, wawancara kepada stakeholders (regulator, asosiasi hotel, akademisi, pengelola hotel, online travel agent, dan wholesaler), serta observasi terhadap sistem BI yang telah ada. Penelitian ini menghasilkan tiga hasil penelitian utama. Untuk memahami konteks ekosistem industri akomodasi, penelitian ini mengkaji penelitian terdahulu dan menghasilkan model downstream supply chain industri akomodasi di Indonesia saat ini. Untuk memahami permasalahan implementasi sistem BI, penelitian ini juga mengkaji dan menghasilkan analisis hambatan menggunakan kerangka kerja Technology Organization Environment (TOE) serta pemetaan tindakan yang dapat dilakukan. Berdasarkan kedua hasil tersebut, penelitian ini mengembangkan sebuah arsitektur dan prototipe high-fidelity sistem BI. Prototipe yang dihasilkan masih berupa front-end berbasis web dan belum sampai kepada pengembangan back-end. Evaluasi arsitektur dilakukan melalui wawancara kepada tujuh narasumber ahli serta pengujian inter-rater reliability kepada 18 responden yang menghasilkan tingkat persetujuan yang sangat baik (koefisien Fleiss-Kappa 0,933). Evaluasi prototipe dilakukan melalui wawancara serta survei System Usability Scale (SUS) yang menghasilkan nilai 74,5 (baik), dan Usability Testing yang menghasilkan nilai 70 (baik). Hasil penelitian ini bermanfaat sebagai panduan bagi regulator dan pelaku industri akomodasi dalam mengembangkan sistem BI yang mendorong kolaborasi data melalui information sharing untuk mendukung proses revenue management di industri akomodasi di Indonesia. Sebagai saran pengembangan, penelitian berikutnya dapat mempelajari aspek-aspek non-fungsionalitas serta mengimplementasikan back-end dan komponen-komponen yang sudah diidentifikasi di dalam arsitektur sistem BI ini.

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One of the challenges faced by the accommodation industry in Indonesia is the difficulty of making decisions based on reliable data and information. Currently, Indonesia does not have comprehensive tourism business data and there is no national-scale tourism information center that can be used by stakeholders. To obtain data, the majority of accommodation managers still practice information sharing manually and have not used an integrated system. This research aims to develop an architecture and prototype (front-end) of information sharing-based business intelligence (BI) systems to support the revenue management process in the accommodation industry in Indonesia. The research approach used is Design Science Research which produces solutions according to the needs of stakeholders in the accommodation sector. Literature review is carried out using the Systematic Literature Review method. Processing and analysis of interview data is carried out using thematic analysis method. Data collection in this study was carried out through observation of tourism data, observation of data on online travel agents, interviews with stakeholders (regulators, hotel associations, academics, hotel managers, online travel agents, and wholesalers), as well as observation of the existing BI system. This study produced three main research results. To understand the context of the accommodation industry ecosystem, this study examines previous research and produces a downstream supply chain model, especially for the current accommodation industry in Indonesia. To understand the BI system implementation problems, this study also examines and produces a barrier analysis using the Technology Organization Environment (TOE) framework as well as mapping actions that can be taken to implement and run the BI system. Based on these two results, this research developed an architecture and prototype of a high-fidelity BI system. The prototype is still a web-based front-end and has not yet reached the back-end development. The architectural evaluation was conducted through interviews with seven experts and inter-rater reliability testing to 18 respondents which resulted in a very good approval rate (Fleiss-Kappa coefficient 0.933). Prototype evaluation was conducted through interviews as well as a System Usability Scale (SUS) survey which resulted in a score of 74.5 (good), and Usability Testing which produced a value of 70 (good). The results of this study are useful as a guide for regulators and accommodation industry players in developing a BI system that encourages data collaboration through information sharing to support the revenue management process in the accommodation industry in Indonesia. Future research can study non-functionality aspects and implement back-end and components that have been identified in this BI system architecture."