Providing a Purchasing System Model for the Sugarcane Development Trading Company and Ancillary Industries

This research was done with the aim of providing the optimal purchasing system model for the sugarcane development trading company and its ancillary industries. This research is a type of mixed exploratory research. In the qualitative phase, the data were analyzed through interviews with 12 people using the snowball and targeted sampling method and with the help of the Foundation's data theory during three stages of open, central and selective coding. Atlas T software was used in qualitative phase data analysis. In the quantitative phase, by using a researcher-made questionnaire with optimal validity and reliability, a total of 284 healthy questionnaires were collected and with the help of the structural equation method with software PLS(Partial Least Squares) was analyzed. Quantitative phase respondents include employees of the logistics, procurement and purchasing department in the sugarcane development company and its functions. These people were selected and surveyed using available sampling method. The findings of the qualitative phase include the presentation of the optimal purchasing system model for the sugarcane development trading company and related industries, which consists of 339 open codes, 62 concepts, and 22 categories. In this context, the criteria of durability, beauty and product packaging, compliance with customer expectations, compatible or environmental products, access to resources, technology, innovation in Product and services, supply and procurement, production, distribution, deregulation and administrative paperwork, order registration and timely delivery of products, indicators and standards of timely delivery have an effect on the central phenomenon of optimal purchasing and the result improved organizational performance, high productivity, improved organizational brand And it leads to efficiency in production. The findings of the quantitative part showed that all the dimensions identified in the qualitative part are significant based on the path coefficients based on the structural equation model and the model has a good fit. For this reason, the qualitative model was confirmed based on quantitative validation.