Luxury: Landscape of Business Administration

Big Data Analytics for Demand Forecasting in the Mushroom Supply Chain

Nicholas Renaldo — 2026-01-01

The mushroom industry plays an increasingly important role in the agri-food sector due to rising demand for nutritious, functional, and sustainable food products. However, the mushroom supply chain faces significant challenges related to perishability, short shelf life, and demand uncertainty, which often result in inventory losses and inefficiencies. This study examines the role of big data analytics capability in enhancing demand forecasting accuracy and its impact on supply chain performance within the mushroom industry. Using a quantitative explanatory research design, data were collected through a structured questionnaire survey of mushroom supply chain actors, including producers, processors, distributors, and retailers. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that big data analytics capability has a significant positive effect on demand forecasting accuracy and supply chain performance. Furthermore, demand forecasting accuracy partially mediates the relationship between big data analytics capability and supply chain performance. These findings highlight the strategic importance of data-driven forecasting in managing demand uncertainty and improving operational efficiency in perishable agribusiness supply chains. This study contributes to the literature by extending big data analytics and demand forecasting research to the mushroom industry, providing both theoretical insights and practical implications for enhancing supply chain sustainability and competitiveness.

Creating Business Value through IoT-Based Waste Management Web Dashboard

Wilda Susanti — 2026-01-05

The rapid growth of urbanization and industrial activities has increased the complexity of waste management operations within business organizations, leading to rising costs and managerial challenges. While the Internet of Things (IoT) has enabled real-time data collection in waste management, business value creation depends on how such data are integrated into managerial information systems. This study aims to develop and evaluate an IoT-based waste management web dashboard that supports operational monitoring and managerial decision-making to create business value. Using a Design Science Research (DSR) methodology, this study designs an integrated system that collects real-time waste volume data through IoT-enabled sensors and presents the information via a centralized web dashboard. The system is evaluated using a mixed approach combining operational performance indicators and user perceptions based on Information Systems Success Theory. The results indicate improvements in operational efficiency, resource allocation, and decision-making quality following system implementation. The findings demonstrate that the proposed web dashboard functions as a strategic managerial information system rather than a purely technical solution. By enhancing information quality and managerial control, the system contributes to business value creation through improved operational performance and supports digital transformation and sustainability-oriented business practices. This study contributes to the business and management literature by shifting the focus of IoT-based waste management research from technical performance to managerial relevance and value creation.

Brand Image, Customer Experience, and Customer Value on Customer Satisfaction at Janji Jiwa Coffee in Pekanbaru City

Amirudin M. Amin — 2026-01-31

This study aims to analyze the influence of brand image, customer experience, and customer value on customer satisfaction of Kopi Janji Jiwa in Pekanbaru City. This study was conducted in Pekanbaru City, with a population of consumers at Kopi Janji Jiwa whose number is unknown. Using the Roscoe method, a sample of 150 people was determined. The sampling technique in this study used accidental sampling. The data analysis method used multiple linear regression. The results of this study indicate that brand image has a significant influence on customer satisfaction of Kopi Janji Jiwa in Pekanbaru City. Furthermore, customer experience has a significant influence on customer satisfaction of Kopi Janji Jiwa in Pekanbaru City and customer value has a significant influence on customer satisfaction of Kopi Janji Jiwa in Pekanbaru City. The adjusted R Square value of 0.550 means that the influence of brand image, customer experience, and customer value on customer satisfaction is 55%, while the remaining 45% is influenced by other variables not used in this study.

Factors Affecting Audit Tenure in Food and Beverage Sub-Sector Companies Listed on the Indonesia Stock Exchange In 2019 – 2023

Anton Anton — 2026-01-31

This study investigates the determinants of audit tenure in Food and Beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period. Specifically, it examines the influence of solvency (Debt to Equity Ratio), profitability (Return on Assets), liquidity (Current Ratio), and firm size (natural logarithm of total assets) on audit tenure. Using purposive sampling, 47 companies were selected, resulting in 235 firm-year observations. The study employs multiple linear regression analysis using SmartPLS 4. The findings indicate that solvency has a positive but statistically insignificant effect on audit tenure, while profitability shows a negative but insignificant relationship. In contrast, liquidity and firm size exhibit a significant negative effect on audit tenure, suggesting that financially stronger and larger firms tend to experience shorter audit tenure periods. However, the model explains only 6% of the variation in audit tenure, indicating that other factors beyond the variables examined may play a more substantial role. This research contributes to the literature on audit timeliness and corporate financial characteristics in emerging markets.

Material Flow Cost Accounting (MFCA)-Driven Smart Goat Livestock Management System

Muhammad Pringgo Prayetno — 2026-01-31

The livestock sector plays a crucial role in food security and rural economic resilience; however, goat farming management in developing economies remains largely traditional and weakly integrated with structured environmental accounting systems. This study develops and validates a Material Flow Cost Accounting (MFCA)-Driven Smart Goat Livestock Management System, which integrates environmental management accounting, Internet of Things (IoT) monitoring, emission estimation, and artificial intelligence (AI)-based decision support within a unified digital platform. Using a design science research approach combined with field validation, the system was implemented in a medium-scale goat farm over a two-month period. The MFCA model quantified material inputs and outputs in both physical and monetary terms, including feed conversion, waste generation, and methane (CH₄) and nitrous oxide (N₂O) emissions based on IPCC Tier 1 guidelines. The results demonstrate improvements in feed efficiency (from 74% to 84%), mortality reduction (from 8% to 4%), increased data accuracy (from 60% to 92%), and a 22% improvement in eco-efficiency ratios. The AI module achieved 87% accuracy in estrus detection and 84% accuracy in early disease classification. The study extends MFCA application from manufacturing to biological production systems and introduces the concept of accounting-driven smart farming, where environmental accounting is embedded within digital infrastructure. The findings contribute to the advancement of Digital Environmental Management Accounting (Digital EMA) and provide a scalable model for sustainable livestock transformation in emerging economies.