The Philippine textile Industry faces significant contraction due to high power costs and foreign competition. This study focuses on Asia Textile Mills, Inc. (ATMI) and its transition toward sustainability using pineapple blended fabrics for pineapple leaf fibers (PALF) to comply withy the Philippine Tropical Fabric Law. Facing challenges in inventory costs and fluctuating demand, the research develops an optimized inventory management framework. Utilizing a quantitative approach, the study employs Time Series Analysis, Naïve Forecasting, and Moving Averages to align raw material procurement with market trends. Furthermore, it integrates ABC Analysis and Lean Principles to categorize inventory and reduce waste. Results demonstrate that driven forecasting and strategic supply chain integration significantly enhance operational efficiency, reduce overstocking, and bolster the global competitiveness of the local textile sector.

Hybrid streetwear brands face a unique problem when balancing inventory, and La Creacion struggles to manage the steady demand for their basic shirts while dealing with the erratic sales of their hand finished art products. To find a practical purchasing strategy, this study implemented the ABC Analysis to group their inventory. Calculations were made with the Economic Order Quantity and Reorder Point. The results have shown that the basic shirts are Class A items that bring in the most money and demand strict control alongside high safety stocks. Meanwhile, the high risk art pieces are categorized as Class C and require minimal stock to avoid high holding costs. By using an appropriate mathematical approach, local micro, small, and medium enterprises can stop relying on intuition and build highly responsive operations that protect the company’s cash flow and keep them financially secure.

In modern supply chain networks, multiple buyers often generate high and uncertain demand, making fixed production policies insufficient for achieving cost efficiency and maintaining product quality. This paper develops a single-vendor multi-buyer supply chain model that incorporates variable production rates, imperfect product quality, service-level constraints, and distribution-free lead-time demand. The unit production cost is assumed to depend on the production rate, and three alternative quality functions are proposed to characterize the relationship between production rate and process quality. The objective is to determine the optimal production and inventory policy that minimizes the total supply chain cost under a single-setup multiple-delivery framework. Closed-form analytical results and an efficient solution algorithm are developed to obtain the optimal decisions. Numerical examples and sensitivity analyses are presented to validate the model and investigate the effects of key parameters. The findings reveal that production-rate flexibility plays a critical role in reducing total supply chain cost while mitigating quality deterioration, providing valuable managerial insights for coordinated supply chain operations.

We formulate the strategic interaction between the regulatory airspace governance and the platform competition in the emerging drone food delivery market of Dubai as a two-stage Stackelberg-Nash game. The regulator (Dubai Civil Aviation Authority), as a Stackelberg leader, sets the quota of airspace slots, the licensing fee per delivery, and the safety threshold to maximize social welfare. After observing the regulatory decisions, two competing food delivery platforms, (Keeta Drone and Talabat), simultaneously choose delivery prices and drone fleet investments as Nash competitors, subject to a shared airspace capacity constraint that links their costs through a congestion externality. We obtain a closed-form Subgame Perfect Nash Equilibrium, and reveal five key propositions characterising the (i) airspace Tragedy of the Commons, (ii) optimal licensing fee, (iii) self-reinforcement of Keeta's cost advantage through coopetition, (iv) strategic complementarity of fleet investments, and (v) safety-investment Pareto complementarity. Finally, using a numerical analysis considering Dubai market data, we quantify welfare losses from market asymmetry, and suggest optimal regulatory policies to DCAA.