IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v11y2026i2p136-148.html

Sort Out: A Smart Inventory Management System Using Descriptive Analytics and Rule-Based Algorithm for Mini Grocery Stores

Author

Listed:
  • Jefferson Suya

    ((SY 2025-2026) Arellano University, Pasig Campus)

  • Gian Carlo Rodillas

    ((SY 2025-2026) Arellano University, Pasig Campus)

  • Xianne Jhuztin Tubog

    ((SY 2025-2026) Arellano University, Pasig Campus)

  • Roland Christopher Doctor

    ((SY 2025-2026) Arellano University, Pasig Campus)

Abstract

This research introduces Sort Out, an Intelligent Inventory Management System tailored to tackle the persistent issues of manual inventory tracking and product management in small grocery stores. Numerous small retailers encounter difficulties like excessive inventory, stockouts, erroneous recordkeeping, and slow reactions to changes in stock levels. To address these challenges, the system combines Descriptive Analytics with a Rule-Based Algorithm to automate essential tasks like product tracking, expiration monitoring, and report creation. The system's design is created according to the System Development Life Cycle (SDLC) approach. Information is collected from chosen mini grocery stores via interviews and observations to identify user needs. The development process employed PHP, MySQL, and XAMPP as main tools, with the interface design refined for ease of use and accessibility.

Suggested Citation

  • Jefferson Suya & Gian Carlo Rodillas & Xianne Jhuztin Tubog & Roland Christopher Doctor, 2026. "Sort Out: A Smart Inventory Management System Using Descriptive Analytics and Rule-Based Algorithm for Mini Grocery Stores," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 11(2), pages 136-148, February.
    • Handle: RePEc:bjf:journl:v:11:y:2026:i:2:p:136-148
    as

    Download full text from publisher

    File URL: https://rsisinternational.org/journals/ijrias/uploads/vol11-iss2-pg136-148-202602_pdf.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrias/view/sort-out-a-smart-inventory-management-system-using-descriptive-analytics-and-rule-based-algorithm-for-mini-grocery-stores/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ron Berman & Ayelet Israeli, 2022. "The Value of Descriptive Analytics: Evidence from Online Retailers," Marketing Science, INFORMS, vol. 41(6), pages 1074-1096, November.
    2. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    3. Meng Qi & Ho‐Yin Mak & Zuo‐Jun Max Shen, 2020. "Data‐driven research in retail operations—A review," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 595-616, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. V. Radhamani & B. Sivakumar & G. Arivarignan, 2022. "A Comparative Study on Replenishment Policies for Perishable Inventory System with Service Facility and Multiple Server Vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 229-265, March.
    2. Chenavaz, Régis & Paraschiv, Corina, 2018. "Dynamic pricing for inventories with reference price effects," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 12, pages 1-16.
    3. Ketzenberg, M.E. & Bloemhof-Ruwaard, J.M., 2009. "The Value of RFID Technology Enabled Information to Manage Perishables," ERIM Report Series Research in Management ERS-2009-020-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Alamri, Adel A. & Syntetos, Aris A., 2018. "Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model," International Journal of Production Economics, Elsevier, vol. 206(C), pages 33-45.
    5. Jo, Wooyong & Lewis, Michael, 2025. "How expansion to the Nintendo Switch impacts PC players’ game usage and spending: A study of an omni-channel strategy," International Journal of Research in Marketing, Elsevier, vol. 42(4), pages 1084-1104.
    6. Richter, K. & Pakhomova, N.V. & Dobos, I., 2006. "A Wagner/Whitin natural resource stock control model," International Journal of Production Economics, Elsevier, vol. 104(2), pages 419-426, December.
    7. Lodree Jr., Emmett J. & Uzochukwu, Benedict M., 2008. "Production planning for a deteriorating item with stochastic demand and consumer choice," International Journal of Production Economics, Elsevier, vol. 116(2), pages 219-232, December.
    8. Alagöz, Nazli, 2024. "Promotion and technological change in the music industry," Other publications TiSEM 511ceba0-62a0-4c60-a76c-f, Tilburg University, School of Economics and Management.
    9. Wu, Jiang & Chang, Chun-Tao & Teng, Jinn-Tsair & Lai, Kuei-Kuei, 2017. "Optimal order quantity and selling price over a product life cycle with deterioration rate linked to expiration date," International Journal of Production Economics, Elsevier, vol. 193(C), pages 343-351.
    10. Ketzenberg, Michael & Oliva, Rogelio & Wang, Yimin & Webster, Scott, 2023. "Retailer inventory data sharing in a fresh product supply chain," European Journal of Operational Research, Elsevier, vol. 307(2), pages 680-693.
    11. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    12. Civelek, Ismail & Karaesmen, Itir & Scheller-Wolf, Alan, 2015. "Blood platelet inventory management with protection levels," European Journal of Operational Research, Elsevier, vol. 243(3), pages 826-838.
    13. Li, Ruihai & Chan, Ya-Lan & Chang, Chun-Tao & Cárdenas-Barrón, Leopoldo Eduardo, 2017. "Pricing and lot-sizing policies for perishable products with advance-cash-credit payments by a discounted cash-flow analysis," International Journal of Production Economics, Elsevier, vol. 193(C), pages 578-589.
    14. Li‐Ming Chen & Amar Sapra, 2013. "Joint inventory and pricing decisions for perishable products with two‐period lifetime," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(5), pages 343-366, August.
    15. Praveendra Singh & Madhu Jain, 2024. "Inventory policy for degrading items under advanced payment with price and memory sensitive demand using metaheuristic techniques," Operational Research, Springer, vol. 24(3), pages 1-34, September.
    16. Lee, Chun Chen, 2006. "Two-warehouse inventory model with deterioration under FIFO dispatching policy," European Journal of Operational Research, Elsevier, vol. 174(2), pages 861-873, October.
    17. José Daniel López-Barrientos & Ekaterina Viktorovna Gromova & Ekaterina Sergeevna Miroshnichenko, 2020. "Resource Exploitation in a Stochastic Horizon under Two Parametric Interpretations," Mathematics, MDPI, vol. 8(7), pages 1-29, July.
    18. Wang, Wan-Chih & Teng, Jinn-Tsair & Lou, Kuo-Ren, 2014. "Seller’s optimal credit period and cycle time in a supply chain for deteriorating items with maximum lifetime," European Journal of Operational Research, Elsevier, vol. 232(2), pages 315-321.
    19. Omar Ahumada & J. Villalobos, 2011. "A tactical model for planning the production and distribution of fresh produce," Annals of Operations Research, Springer, vol. 190(1), pages 339-358, October.
    20. Duan, Qinglin & Liao, T. Warren, 2013. "A new age-based replenishment policy for supply chain inventory optimization of highly perishable products," International Journal of Production Economics, Elsevier, vol. 145(2), pages 658-671.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:journl:v:11:y:2026:i:2:p:136-148. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.