Journal of Sustainability Industrial Engineering and Management System
Journal of Sustainability Industrial Engineering and Management System is an interdisciplinary academic journal devoted to the publication of high-quality research and contributions to the industrial engineering and management community. The major focus are: - To collect and disseminate information on new and advanced developments in the field of industrial engineering and management; - To encourage further progress in engineering and management methodology and applications; - To cover the range of engineering and management development and usage in their use of managerial policies and strategies. Journal of Sustainability Industrial Engineering and Management System invites the submission of original, high-quality, theoretical, and application-oriented research; general surveys and critical reviews; educational or training articles, including case studies, in the field of industrial engineering and management. - Design and Manufacturing Engineering, - Facilities Engineering, Environment, and Energy - Production Systems, - Operations Research & Analysis, - Service Engineering, - Application of Artificial Intelligence in Industrial Engineering and Management, - Automation, Robotics, and Mechatronics, - Information and Communication Systems, - ICT for Collaborative Manufacturing, - Computational modelling, - Applied Statistics and Data Mining, - Quality and Reliability Engineering, - Human Factors, Ergonomics, and Safety, - Work Design and Measurement, - System Design and Engineering, - Organization and Human Resources, - Engineering Management, - Entrepreneurship and Innovation, - Inventory, Logistics, and Transportation, - Project Management, - Supply Chain Management, - Risk Management, - Asset Pricing Models and Portfolio Optimization, - Marketing and Commerce, - Investment, Finance, and Accounting, - Insurance Engineering and Management, - Media Engineering and Management, - Education and Practices in Industrial Engineering and Management, - Other Related Subject.
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<![CDATA[A Qualitative Exploration of Predictive Maintenance Practices in Bali ]]>
<![CDATA[Wiratama, Bayu]]>
<![CDATA[ Journal of Sustainability Industrial Engineering and Management System Vol. 2 No. 2 (2024): January - June ]]>
Publisher : <![CDATA[Omnia Tempus ]]>
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DOI: 10.56953/jsiems.v2i2.32
<![CDATA[This study investigates the practices, challenges, and strategic implications of predictive maintenance (PdM) in the industrial sector of Bali, Indonesia, with a particular emphasis on how local organizations conceptualize, implement, and experience PdM within their socio-technical contexts. The research aims to bridge the knowledge gap between global technological paradigms and localized maintenance strategies by exploring the extent to which PdM has been integrated into organizational routines and infrastructure. Employing a qualitative research design grounded in the interpretive paradigm, the study adopts an exploratory case study approach. Data were collected through in-depth semi-structured interviews, document analysis, and site observations across multiple firms in the manufacturing, utility, and infrastructure sectors. Thematic analysis was conducted using NVivo 14, ensuring methodological rigor and triangulation of findings. The study reveals significant variations in organizational awareness, technological readiness, and human capital development related to PdM adoption. Key findings highlight the misalignment between technological investments and actual utilization, as well as the pivotal role of leadership and organizational culture in shaping implementation outcomes. Moreover, the research identifies infrastructural limitations, digital literacy gaps, and vendor dependencies as major constraints, especially for small and medium-sized enterprises. Notably, several firms demonstrated emerging alignment between PdM practices and sustainability goals, suggesting untapped potential for predictive strategies to contribute to broader environmental and operational performance. The study concludes that successful PdM implementation in Bali requires a synergistic combination of technical infrastructure, cultural transformation, and strategic alignment, supported by cross-sectoral collaboration and policy intervention. These insights contribute to the evolving discourse on smart maintenance in emerging economies and offer practical recommendations for industrial managers, policymakers, and technology providers.]]>
<![CDATA[Automation and Skill Shift: Understanding the Workplace Transformation ]]>
<![CDATA[Rahmadina, Tasya]]>
<![CDATA[ Journal of Sustainability Industrial Engineering and Management System Vol. 2 No. 2 (2024): January - June ]]>
Publisher : <![CDATA[Omnia Tempus ]]>
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DOI: 10.56953/jsiems.v2i2.33
<![CDATA[This study explores the evolving dynamics of workforce transformation amid accelerating automation and the ensuing shift in skill demands. In an era characterized by rapid technological advancement, automation is redefining not only job roles but also the parameters of employability across industries. The research adopts a qualitative, literature-based methodology grounded in interpretive analysis to examine the socio-technical implications of automation on the nature of work, particularly the emergence of new skill requirements and organizational adaptation strategies. By reviewing and synthesizing insights from approximately 60 scholarly sources published between 2010 and 2024, the study employs thematic content analysis to identify patterns related to job reconfiguration, skill shifts, and institutional responses. The findings reveal that automation primarily restructures rather than replaces jobs, reallocating routine tasks to machines while intensifying the cognitive and emotional demands placed on human workers. Moreover, the study underscores the growing importance of digital literacy, emotional intelligence, adaptability, and continuous learning as essential competencies in the modern workplace. Institutional readiness—manifested through policy reform, educational innovation, and proactive organizational strategy—is found to be a critical determinant of whether automation leads to empowerment or displacement. The research concludes that sustainable workforce transformation requires an integrated, human-centered approach that aligns technological deployment with inclusive and adaptive systems of education and employment. This study contributes to the broader discourse by offering a nuanced, context-sensitive understanding of how automation is currently reshaping labor markets, while advocating for ethical and inclusive frameworks to guide future transitions.]]>
<![CDATA[Cloud-Based ERP Implementation Challenges in Small Industries ]]>
<![CDATA[Handoko, Yusuf]]>
<![CDATA[ Journal of Sustainability Industrial Engineering and Management System Vol. 2 No. 2 (2024): January - June ]]>
Publisher : <![CDATA[Omnia Tempus ]]>
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DOI: 10.56953/jsiems.v2i2.34
<![CDATA[This study investigates the multifaceted challenges faced by small industries in implementing cloud-based Enterprise Resource Planning (ERP) systems, aiming to provide a comprehensive understanding of the technical, organizational, and human-centric barriers that hinder adoption. Employing a qualitative research design, the study adopts an interpretivist approach through a systematic literature review of 45 peer-reviewed articles published between 2010 and 2024. Data were analyzed thematically using ATLAS.ti, enabling the identification of key implementation challenges and contextual factors shaping ERP adoption in resource-constrained industrial environments. The findings reveal three primary categories of obstacles: infrastructure and technological deficiencies, organizational unreadiness coupled with resistance to change, and significant human resource and knowledge gaps. Specifically, the study finds that inadequate digital infrastructure, cultural inertia, and the absence of sustained training programs frequently result in project delays, underutilized systems, and operational inefficiencies. Moreover, cloud-based ERP systems' success depends heavily on contextual alignment with the firm’s internal capabilities, strategic planning processes, and commitment to long-term digital transformation. These insights contribute to existing theoretical models such as the Technology-Organization-Environment (TOE) framework by highlighting the role of sustainability-oriented digital strategies and adaptive implementation practices. The study recommends collaborative interventions among policymakers, vendors, and industry associations to address structural disparities and to foster inclusive technological ecosystems. The research contributes both theoretically and practically to the discourse on ERP adoption, particularly within emerging markets where small industries remain foundational to economic development.]]>
<![CDATA[Organizational Challenges in Quality Assurance among Food Startups ]]>
<![CDATA[Lestiani, Amira]]>
<![CDATA[ Journal of Sustainability Industrial Engineering and Management System Vol. 2 No. 2 (2024): January - June ]]>
Publisher : <![CDATA[Omnia Tempus ]]>
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DOI: 10.56953/jsiems.v2i2.35
<![CDATA[This study explores the organizational challenges in quality assurance (QA) encountered by food startups operating within resource-constrained and rapidly evolving business environments. As consumer expectations for food safety and regulatory compliance intensify, startups face significant pressure to institutionalize effective QA systems. However, their informal structures, limited capital, and lack of specialized expertise often result in ad hoc quality practices that threaten operational integrity and customer trust. The objective of this research is to examine how internal organizational dynamics—such as leadership commitment, resource allocation, staff competencies, and learning capacity—affect QA implementation in food startups. Employing a qualitative methodology through literature-based analysis, the study systematically synthesizes academic articles, case studies, and regulatory reports to identify recurring themes and structural impediments. Findings reveal four major organizational challenges: weak quality culture and leadership, inadequate infrastructure and human resources, complex regulatory landscapes, and limited scalability of QA systems. These challenges are shown to interact in mutually reinforcing ways, exacerbating quality risks as startups grow. The study also uncovers a critical gap in quality learning mechanisms that prevents startups from evolving toward maturity. The results underscore the need for tailored QA frameworks and policy support to foster sustainable quality practices. The study contributes to the theoretical understanding of QA in emerging business contexts and offers managerial insights for founders, incubators, and regulators aiming to strengthen quality foundations in the food startup ecosystem.]]>
<![CDATA[Adapting Statistical Thinking in Traditional Manufacturing Contexts ]]>
<![CDATA[Nugroho, Fajar]]>
<![CDATA[ Journal of Sustainability Industrial Engineering and Management System Vol. 2 No. 2 (2024): January - June ]]>
Publisher : <![CDATA[Omnia Tempus ]]>
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DOI: 10.56953/jsiems.v2i2.36
<![CDATA[This study explores the adaptation of statistical thinking in traditional manufacturing contexts, emphasizing its significance as a cognitive and cultural framework for improving quality, reducing process variation, and fostering data-informed decision-making. While statistical thinking has become a cornerstone in modern manufacturing systems, its integration into traditional environments—dominated by legacy processes, experiential judgment, and minimal technological infrastructure—remains limited. The purpose of this research is to analyze the current landscape of statistical awareness in such settings and to identify both enablers and barriers to its broader adoption. Employing a qualitative methodology based on an integrative literature review, this study synthesizes evidence from peer-reviewed articles, industry case studies, and theoretical frameworks published between 2000 and 2024. Thematic analysis reveals a persistent gap in statistical literacy among employees, cultural resistance among leaders, and technological limitations that impede implementation. However, emerging practices—such as contextualized training, policy interventions, and leadership-driven cultural change—offer promising pathways for sustainable integration. The findings contribute to both academic and managerial discourse by reframing statistical thinking as a holistic organizational capability rather than a technical function. This research advocates for a strategic and inclusive approach that combines education, infrastructure, and leadership to foster statistical maturity in resource-constrained manufacturing environments. In doing so, it supports long-term resilience, continuous improvement, and competitiveness in the face of global industrial transformation.]]>
