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MARKOV PROCESS AND CREDIT COLLECTION POLICY *
Author(s) -
MEHTA DILEEP
Publication year - 1972
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1972.tb00534.x
Subject(s) - cash flow , process (computing) , computer science , consistency (knowledge bases) , debt , data collection , markov process , transient (computer programming) , markov decision process , function (biology) , business , finance , economics , operations research , mathematics , artificial intelligence , statistics , evolutionary biology , biology , operating system
This paper deals with the evaluation of credit collection policy alternatives, given the credit granting function. Credit collection policy determines the intensity of collection efforts and the timing for recognition of bad debts. The Markov Process is utilized to estimate dynamic cash flow behavior for available policy alternatives. For this purpose, both transient and steady‐state components of cash‐flow behavior are considered. Operational guidelines are outlined with the help of a single example. The strength of the proposed model stems from its a) consistency with the conventional capital budgeting process, b) modest input data requirements, and c) expediency in obtaining results.