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Analysis of the Effect of Sustainable Marketing Strategy, Brand Image, and Customer Satisfaction on Customer Loyalty in the Manufacturing Industry in Karawang Sudirjo, Frans; Mu'min, Halek; Marjuki, Marjuki; Triyantoro , Andri
West Science Interdisciplinary Studies Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i02.674

Abstract

This research investigates the dynamics of Sustainable Marketing Strategy, Brand Image, Customer Satisfaction, and their collective impact on Customer Loyalty in the manufacturing industry in Karawang. A quantitative analysis, employing Structural Equation Modeling (SEM-PLS), was conducted on a sample of 250 manufacturing firms. The results reveal statistically significant relationships: Sustainable Marketing Strategy positively influences Brand Image, Customer Satisfaction, and ultimately, Customer Loyalty. Brand Image and Customer Satisfaction also exhibit direct positive impacts on Customer Loyalty. The findings offer strategic insights for firms to navigate the competitive landscape by emphasizing sustainable practices, brand building, and a customer-centric approach. Policymakers can leverage these insights to advocate for sustainable development within the manufacturing sector, contributing to both economic and environmental sustainability.
Analysis of the Effect of Sustainable Marketing Strategy, Brand Image, and Customer Satisfaction on Customer Loyalty in the Manufacturing Industry in Karawang Sudirjo, Frans; Mu'min, Halek; Marjuki, Marjuki; Triyantoro , Andri
West Science Interdisciplinary Studies Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i02.674

Abstract

This research investigates the dynamics of Sustainable Marketing Strategy, Brand Image, Customer Satisfaction, and their collective impact on Customer Loyalty in the manufacturing industry in Karawang. A quantitative analysis, employing Structural Equation Modeling (SEM-PLS), was conducted on a sample of 250 manufacturing firms. The results reveal statistically significant relationships: Sustainable Marketing Strategy positively influences Brand Image, Customer Satisfaction, and ultimately, Customer Loyalty. Brand Image and Customer Satisfaction also exhibit direct positive impacts on Customer Loyalty. The findings offer strategic insights for firms to navigate the competitive landscape by emphasizing sustainable practices, brand building, and a customer-centric approach. Policymakers can leverage these insights to advocate for sustainable development within the manufacturing sector, contributing to both economic and environmental sustainability.
Analysis of the Effect of Sustainable Marketing Strategy, Brand Image, and Customer Satisfaction on Customer Loyalty in the Manufacturing Industry in Karawang Sudirjo, Frans; Mu'min, Halek; Marjuki, Marjuki; Triyantoro , Andri
West Science Interdisciplinary Studies Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i02.674

Abstract

This research investigates the dynamics of Sustainable Marketing Strategy, Brand Image, Customer Satisfaction, and their collective impact on Customer Loyalty in the manufacturing industry in Karawang. A quantitative analysis, employing Structural Equation Modeling (SEM-PLS), was conducted on a sample of 250 manufacturing firms. The results reveal statistically significant relationships: Sustainable Marketing Strategy positively influences Brand Image, Customer Satisfaction, and ultimately, Customer Loyalty. Brand Image and Customer Satisfaction also exhibit direct positive impacts on Customer Loyalty. The findings offer strategic insights for firms to navigate the competitive landscape by emphasizing sustainable practices, brand building, and a customer-centric approach. Policymakers can leverage these insights to advocate for sustainable development within the manufacturing sector, contributing to both economic and environmental sustainability.
Ethical and Legal Analysis of Artificial Intelligence Systems in Law Enforcement with a Study of Potential Human Rights Violations in Indonesia Zuwanda, Zulkham Sadat; Lubis, Arief Fahmi; Solapari, Nuryati; Sakmaf, Marius Supriyanto; Triyantoro , Andri
The Easta Journal Law and Human Rights Vol. 2 No. 03 (2024): The Easta Journal Law and Human Rights (ESLHR)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/eslhr.v2i03.283

Abstract

This research examines the ethical and legal implications of deploying Artificial Intelligence (AI) systems in law enforcement, with a particular focus on potential human rights violations in Indonesia. Utilizing a normative analysis approach, the study evaluates existing ethical frameworks, legal principles, and human rights standards to assess the governance and implications of AI-driven policing. Key findings indicate significant ethical concerns, including bias, discrimination, lack of transparency, and privacy violations. The legal analysis reveals gaps in Indonesia’s regulatory framework, highlighting the need for specific legislation to address AI’s complexities. Human rights implications, such as threats to privacy, freedom of expression, and equality, are critically analyzed. Comparative case studies from other jurisdictions provide empirical insights and underscore the importance of robust ethical and legal frameworks. The research proposes several recommendations, including the establishment of clear ethical guidelines, strengthening legal frameworks, enhancing transparency and accountability, promoting public engagement, and conducting regular impact assessments to ensure responsible AI governance in law enforcement. This study aims to contribute to the development of ethical AI governance frameworks and inform policy recommendations for responsible AI deployment in law enforcement practices.