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Ikhsan Nendi
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Hospitality Management and Operations Journal
Published by Politeknik Siber Cerdika Internasional
ISSN : -     EISSN : 30898846     DOI : https://doi.org/10.59261/hmoj.v1i1
Core Subject : Science,
Decision Sciences, Operations Research & Management
The scope of the journal includes, but is not limited to: Hospitality Operations Management Hotel and Restaurant Management Tourism Development and Sustainability Customer Service Excellence Technology in Hospitality Human Resource Management in Hospitality Hospitality Marketing and Strategy Hospitality and Tourism Education Revenue and Financial Management in Hospitality Innovative Trends in Hospitality Industry
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Tourism, Leisure and Hospitality Management
Articles 14 Documents
 1   2 
Enhancing Service Operations Efficiency Through Data-Driven Decision Making: Evidence from Full-Service Hotels in Southeast Asia Dwi Savandha, Septien
Hospitality Management and Operations Journal Vol. 2 No. 2 (2025): Hospitality Management and Operations Journal
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/hmoj.v2i2.45

Abstract

The rapid expansion of the hospitality industry in Southeast Asia, driven by significant growth in international arrivals and evolving digital expectations, has heightened the need for service operations that are both efficient and data-driven. Despite advancements in digital infrastructure, many full-service hotels in the region continue to experience operational inefficiencies due to fragmented data systems, limited analytical competencies, and weak integration of data insights into managerial decision-making. This study investigates how data-driven decision making (DDDM) enhances service operations efficiency in full-service hotels across Southeast Asia by examining the extent of analytical adoption and its operational impact. A mixed-methods approach is employed, combining quantitative assessments of operational efficiency indicators with qualitative insights from hotel managers and frontline supervisors. The study integrates multiple operational dimensions labor scheduling, housekeeping performance, inventory control, guest service responsiveness, and revenue optimization to provide a holistic evaluation of DDDM effectiveness. Findings reveal that hotels implementing advanced data-driven practices achieve substantial gains in labor productivity, faster service response times, and improved resource utilization compared to hotels that rely on manual or non-integrated systems. Contextual factors such as staff analytical capability, digital infrastructure maturity, and leadership commitment significantly moderate the effectiveness of DDDM. This study contributes to hospitality management literature by offering the first integrated empirical framework linking DDDM with multidimensional service operations efficiency in Southeast Asian full-service hotels. Practical recommendations are provided to guide hotel leaders in designing data-driven strategies that improve operational performance and strengthen competitive advantage in an increasingly digital hospitality landscape.
Adopting AI-Powered Automation for Optimizing Hotel Operational Performance: A Cross-Country Comparative Study Ratnasari, Wahyu; Astuti, Yuli
Hospitality Management and Operations Journal Vol. 2 No. 2 (2025): Hospitality Management and Operations Journal
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/hmoj.v2i2.46

Abstract

Rapid advancements in artificial intelligence (AI) and service automation have transformed operational models in the global hospitality industry. Hotels increasingly implement AI-powered technologies such as automated check-in systems, service robots, predictive analytics, and intelligent housekeeping tools to enhance efficiency, reduce labor costs, and improve service quality. However, AI adoption varies significantly across countries due to differences in digital readiness, cultural acceptance, workforce adaptability, and investment capacity. This study aims to examine how AI-powered automation influences hotel operational performance across countries with different levels of technological maturity. A comparative study across five countries examined operational metrics and managerial insights from 210 hotels. The findings reveal that AI adoption enhances operational performance across all countries, though to varying degrees. Hotels in high-adoption countries reported up to a 45% improvement in operational efficiency, while those in emerging economies achieved 18–25% gains, constrained mainly by infrastructural and organizational factors. The study concludes that AI-powered automation delivers substantial operational benefits, but its effectiveness depends on contextual factors, including digital infrastructure, investment capacity, and cultural acceptance. This research contributes to the hospitality management literature by offering one of the first empirical, multi-country models explaining differential AI performance outcomes and by providing strategic guidance for hotel managers planning AI integration across diverse markets.
Sustainable Operations Management in Hospitality: An Empirical Study of Energy Efficiency and Waste Reduction Strategies Handayani, Tri
Hospitality Management and Operations Journal Vol. 2 No. 2 (2025): Hospitality Management and Operations Journal
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/hmoj.v2i2.47

Abstract

The hospitality industry faces mounting pressure to enhance sustainability performance amid escalating environmental degradation, resource depletion, and operational costs. Hotels are resource-intensive establishments that consume substantial energy and generate considerable waste through continuous 24-hour operations and high guest turnover. This study investigates the implementation and effectiveness of integrated energy-efficiency and waste-reduction strategies within hotel operations, addressing the persistent gap between environmental intentions and operational practices today.  Employing a cross-sectional design, this research utilizes Structural Equation Modeling (SEM) and multiple regression analysis on primary data from 150 hotel managers across Indonesian properties. The measurement instrument demonstrates robust validity through Confirmatory Factor Analysis (factor loadings: 0.68-0.89, AVE: 0.58-0.72) and reliability (Cronbach's ?: 0.81-0.89, Composite Reliability: 0.82-0.90).  Results reveal that energy-efficiency practices (?=0.47, p<0.001, R²=0.34) and waste-reduction strategies (?=0.52, p<0.001, R²=0.41) significantly enhance operational performance. The integrated sustainability model demonstrates superior explanatory power (R²=0.57), with waste reduction exerting a more substantial effect (?=0.44) than energy efficiency (?=0.31). Hotels implementing formal sustainability policies consistently outperform non-policy hotels across all performance dimensions. This research provides empirical evidence on integrated operational frameworks, performance-based sustainability assessment, and applicability in emerging economies. Findings underscore that coordinated energy and waste management initiatives constitute essential pathways toward operational resilience and competitive advantage in hospitality operations.
Digital Transformation in Hospitality Operations: Evaluating the Effectiveness of Smart Service Technologies in Urban Hotels Ahmad Zainunnuri, Fakhri
Hospitality Management and Operations Journal Vol. 2 No. 2 (2025): Hospitality Management and Operations Journal
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/hmoj.v2i2.49

Abstract

Digital transformation is reshaping hospitality operations, particularly in urban hotels where technological innovation is increasingly essential for maintaining service quality and competitiveness. This study evaluates the effectiveness of innovative service technologies—such as contactless systems, AI-driven personalization, automated service platforms, and IoT-enabled room features—in enhancing operational performance and guest experience. A quantitative research design was employed, using a structured questionnaire distributed to 200 guests who had recently stayed in urban hotels implementing innovative services. Data were analyzed using Structural Equation Modeling (SEM) to assess relationships among smart service attributes, technology acceptance, operational efficiency, and guest satisfaction. The results show that usability and reliability are the strongest-performing attributes, significantly influencing technology acceptance. Technology acceptance was found to mediate the relationships among smart service attributes, operational efficiency, and guest satisfaction, underscoring its pivotal role in digital adoption. Innovative services also demonstrated a substantial positive impact on service delivery speed, process accuracy, and workload reduction. Comparative analysis indicated significant differences in usability and satisfaction across age groups and stay frequency. Overall, the findings validate the conceptual framework and emphasize the importance of user-centered technological design, trust-building, and personalized digital experiences. This study contributes theoretical insights into innovative hospitality systems and provides practical guidance for hotels seeking to optimize digital transformation strategies in urban environments.

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