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"The rapid evolution of digital technologies is reshaping the marketing landscape, presenting unprecedented opportunities and complex challenges for businesses. This study explores the strategic implications of digital technology dynamics, focusing on their transformative impact on marketing strategies, consumer behaviour, and business practices by examining key technological advancements, including Artificial Intelligence (AI), Internet of Things (IoT), robotics, and social media platforms. The paper highlights how these innovations are driving personalizations, enhancing costumers experiences, and fostering operational efficiency. The study integrates concepts from Marketing 5.0, Industry 5.0, and Society 5.0 to establish a comprehensive framework that connects technological progress with marketing innovation. Findings indicate that AI and big data analytics enable predictive insights and customized interactions. In contrast, concerns surrounding data privacy and the ethical use of technology underscore the need for responsible innovation. Additionally, the study examines how techonology influences the role of marketing professionals, emphasizing the importance of adaptability and AI compatibility for future practitioners. This research provides actionable insights for marketers and organizations, suggesting strategies to leverage digital technologies for competitive advantage. It also identifies opportunities for interdisciplinary research to deepen understanding of the interplay between technology and marketing. By adressing the strategic integration of emerging technologies, this paper contributes to the broader discourse on sustainable and consumer-centric marketing in an era of continuous technological advancement."

"Seiring perkembangan teknologi informasi, adanya kebutuhan untuk menilai kesiapan pemerintah dalam menghadapi transformasi digital. Saat ini di Indonesia hanya memiliki penilaian Sistem Pemerintahan Berbasis Elektronik (SPBE) sebagai alat ukur dalam transformasi digital di pemerintahan. Namun, indeks SPBE yang ada saat ini memiliki beberapa keterbatasan, yakni terfokus pada aspek teknis dan administratif, kurang memperhatikan kualitas layanan publik, tidak mencukupi untuk mengukur partisipasi dan kolaborasi publik, serta tidak mencakup aspek budaya organisasi dan peningkatan kapasitas sumber daya manusia. Sehingga, penelitian ini bertujuan untuk mengembangkan model pengukuran kesiapan transformasi digital di pemerintahan Indonesia dengan mengidentifikasi faktor-faktor yang relevan. Penelitian ini menggunakan metodologi mixed method, dimulai dengan tinjauan literatur untuk mengidentifikasi faktor-faktor yang mempengaruhi kesiapan transformasi digital. Faktor-faktor ini kemudian divalidasi melalui expert judgment menggunakan metode Analytic Hierarchy Process (AHP). Selanjutnya, dilakukan analisis kuantitatif menggunakan Principal Component Analysis (PCA) dan Confirmatory Factor Analysis (CFA) untuk menguji model yang diusulkan. Penelitian ini menggunakan metode purposive sampling untuk memilih sampel, sebanyak 137 responden dari berbagai instansi pemerintah di Indonesia berpartisipasi dalam survei ini. Hasil analisis menunjukkan bahwa model pengukuran kesiapan transformasi digital terdiri dari lima faktor utama: teknologi, organisasi, lingkungan, people, dan user, dengan total 22 sub faktor. Pengujian model menunjukkan bahwa model yang dihasilkan memiliki nilai Tucker-Lewis Index (TLI) sebesar 0.905 dan Comparative Fit Index (CFI) sebesar 0.918, yang menunjukkan bahwa model memiliki tingkat good fit. Hasil penelitian ini diharapkan dapat digunakan sebagai kerangka kerja untuk menilai kesiapan transformasi digital di pemerintahan Indonesia. Model ini diharapkan dapat membantu pemerintah dalam mengidentifikasi faktor-faktor krusial yang perlu diperhatikan untuk meningkatkan mutu layanan publik dan efektivitas strategi digital mereka. Penelitian ini memberikan kontribusi penting dalam bidang transformasi digital di sektor publik dan menawarkan panduan praktis bagi pemerintah untuk mengimplementasikan transformasi digital secara lebih efektif dan efisien.

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With the development of information technology, there is a need to assess the readiness of governments to face digital transformation. Currently in Indonesia, the only assessment tool for digital transformation in government is the Electronic Government System (SPBE) assessment. However, the current SPBE index has several limitations: it focuses mainly on technical and administrative aspects, pays insufficient attention to public service quality, fails to measure public participation and collaboration adequately, and does not cover organizational culture and human resource capacity building aspects. Therefore, this research aims to develop a model for measuring digital transformation readiness in the Indonesian government by identifying relevant factors. This study employs a mixed-method methodology, starting with a literature review to identify factors influencing digital transformation readiness. These factors are then validated through expert judgment using the Analytic Hierarchy Process (AHP). Subsequently, quantitative analysis is conducted using Principal Component Analysis (PCA) and Confirmatory Factor Analysis (CFA) to test the proposed model. The study utilizes purposive sampling to select a sample of 137 respondents from various government agencies in Indonesia who participated in the survey. The analysis results indicate that the digital transformation readiness measurement model consists of five main factors: technology, organization, environment, people, and user, with a total of 22 sub-factors. Testing of the model shows that the resulting model has a Tucker-Lewis Index (TLI) of 0.905 and a Comparative Fit Index (CFI) of 0.918, indicating a good fit. This research is expected to serve as a framework for assessing digital transformation readiness in the Indonesian government. The model is intended to assist governments in identifying crucial factors to enhance public service quality and the effectiveness of their digital strategies. This study provides significant contributions to the field of digital transformation in the public sector and offers practical guidance for governments to implement digital transformation more effectively and efficiently."

"Bersamaan dengan adanya perkembangan teknologi saat ini, bentuk turunan transformasi digital korporat Divisi Umum Dan Aset Properti (DIV MUM) PT XYZ Kantor Pusat melakukan pengembangan dalam bentuk program aplikasi transformation digital general affairs. Adanya transformasi digital tidak hanya mampu mengurangi biaya operasional dan meningkatkan produktivitas namun juga mampu memperkuat daya saing antar perusahaan dan kinerja secara keseluruhan. Pada penelitian ini menggunakan analisis kualitatif, dengan teknik pengumpulan data pada penelitian ini menggunakan mixed method. Unit analisis yang digunakan yaitu unit analisis data adalah single unit dengan single case study. Hasil pemetaan risiko menyatakan bahwa terdapat 3 risiko yang masuk kedalam kategori “extreme”, 9 risiko masuk kedalam kategori ”high”, 5 risiko masuk kedalam kategori ”medium”, dan 11 risiko masuk kedalam kategori ”very low”. Kemudian hasil pemetaan dapat menentukan risiko prioritas dari proses pengembangan aplikasi GA Service, terdapat 17 risiko.

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Along with the current technological developments, a derivative form of corporate digital transformation of the General and Property Assets Division (DIV MUM) of PT XYZ Head Office is developing in the form of a digital transformation general affairs application program. This research is interesting to study, in addition to the risks that need to be mapped first, this application can be a cost reduction for the company. This research uses qualitative analysis, with data collection techniques using mixed methods. The unit of analysis used a single unit with a single case study. The risk mapping results show three risks that fall into the "extreme" category, nine risks fall into the "high" category, five risks fall into the "medium" category, and eleven risks fall into the "very low" category. Then the mapping results can determine the priority risks of the GA Service application development process, there are seventeen risks."