LOGISTICAL MODELING OF CUSTOMER SERVICE PROCESSES IN TRAVEL COMPANIES UNDER CONDITIONS OF UNEVEN DEMAND

Abstract

The scientific article is strictly devoted to solving an urgent scientific and practical problem of increasing the efficiency of customer service during the formulation and sale of complex tourism products in a dynamic market environment. The study fully substantiates the expediency of using the mathematical apparatus of the queuing theory to optimize interaction processes between tour operators, travel agents, and end customers. The author carefully formalizes the integrated logistics chain of tour organization and sales as a complex multi-criteria queuing system with waiting and a limited queue length. During the structural modeling process, the key operational parameters of the customer service system functioning are identified and mathematically described. In particular, such critical factors as the intensity of the incoming request stream, the average time of technical and advisory order processing by managers, and the probability of service denial due to system overload are taken into account. It is explicitly shown that modeling service processes under uneven demand conditions forms a reliable basis for stabilizing operational activity, while the optimal service level and standards rely directly on the fundamental principles and regularities of choice psychology and customer interaction timing. It is firmly established that one of the critical indicators of customer service quality is the speed of initial response to requests and the timeliness of communication at all stages of sales, which creates an objective necessity for implementing effective queue management tools. The article presents a robust, step-by-step mathematical algorithm for determining the optimal number of service channels. The main objective of this algorithm is to minimize the total costs of a travel company, which integrates two components: direct costs of maintaining and expanding service channels, and indirect financial losses from the permanent loss of potential customers due to long waiting times. The obtained research results should be implemented into the daily operations of tourism companies to forecast service failures and increase tourist loyalty.