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Product feature as a determinant of the industrial buying method

Celińska Anna

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

2020

z. 148

89--101

Purpose: The purpose is to present how a product feature, as determinant, affects selection of the appropriate buying method. The correct buying method choice provides companies with many advantages in terms of cost savings achieved within the organisation. Design/methodology/approach: The main method used is case study. The measurement of the result is based on target achievement set by a company. In addition the article reveals a new mathematical analysis of learning curve using integral calculation. Findings: Two determinants are presented – vulnerability to engineering changes and high labour intensity. Analyses show that choosing adequate buying method to a certain purchasing situation influences cost performance. There is also deliberation of new mathematical analysis of learning curve as supportive tool for industrial buyer. Research limitations/implications: The main limitation of this research is impossibility to test effectiveness of using different buying methods scenarios under the same conditions. Practical implications: For practitioners, buying method should be carefully chosen in relation to certain purchasing situation, e.g. product feature should be considered as one of the determinants. The article also provides supportive tool for price negotiations using learning curve phenomenon. Originality/value: The article presents how two determinants, frequent engineering changes and high labour intensity, affecting optimal industrial buying method selection in order to achieve better cost performance. In addition the article revealed new mathematical analysis of learning curve as supportive tool for professional buyers to be used during direct negotiations with suppliers.

Effect of demand boosting policy on optimal inventory policy for imperfect lot size with backorder in fuzzy environment

Yadav D., Singh S. R., Kumari R.

Control and Cybernetics

2012

Vol. 41, no. 1

191-212

This paper investigates an Economic Order Quantity (EOQ) model with backorder by taking imprecise demand rate with dependence upon the frequency of advertisement. The formulated model also incorporates learning effects on percentage of defective items present in each lot. Due to imprecision in demand, the obtained profit function is fuzzy. To determine the optimal values, we determine the equivalent crisp profit function by applying the signed distance method. Optimal order quantity and backorder level are obtained by using algebraic method in place of differential calculus. A numerical example is used to study the behavior of the model with respect to different inventory parameters. All calculations are performed with MATLAB 7.4.