Andrii Chukhrai

The constant change in consumer preferences requires adjusting sales strategies according to the consumer’s current needs. The study aims to cluster the consumers of tourism products based on the factors influencing their decision-making process when choosing tourism products and to classify them according to the marketing mix. The study is based on the analysis of data from 196 respondents in the Lviv region, collected through an online survey using Google Forms in the first decade of 2023. The sample is representative, as it was calculated considering the population of the Lviv region aged 16 and above, ensuring the results’ reliability and relevance. The results revealed that representatives of each cluster are, on average, willing to spend up to 10,000 UAH per person during their vacation. In the decision-making process regarding the purchase of components of a tourist product, accommodation holds the most significant importance for representatives of the first and second clusters (4.51 and 3.27, respectively), insurance is the most important for the third cluster (4.71), and food is the priority for the fourth cluster (2.54). The decisive components of tourist services and risks for all clusters include up-to-date information about the vacation destination and pandemics/diseases, although the significance of their influence varies. Additionally, the clusters differ regarding the elements of place and promotion of tourist products. The results demonstrate that the marketing mix elements vary across clusters despite certain similarities in respondents’ assessments.

Type of the article: Research Article

Abstract
The complexity of industrial markets in the Fourth Industrial Revolution necessitates new pricing approaches for R&D outcomes. “Technology-push” innovations often feature advanced technical parameters that are misaligned with customers’ willingness to pay, creating a commercialization gap that requires models that integrate cost, competition, and perceived value. The aim of this study is to develop a price-determining model for industrial “technology-push” innovations. The authors’ price-determining model for industrial “technology-push” innovations combines cost-plus pricing and competitive pricing with the Price Sensitivity Measurement (PSM) analysis. Empirical data from 2022 to 2025 in optical interferometry were used to validate the approach. In the case of “technology-push” innovations, a gap may exist between the perceived value of technical parameters and the price that industrial customers are willing to pay. The trade-off between technical parameters and price refers to the balance or compromise that customers and industrial marketers must consider when making a purchase. Setting the right price on industrial “technology-push” products requires a comprehensive analysis of customer preferences, competitive landscape, and cost structures. Customers’ perception of value directly influences their willingness to pay for a product or service. Even if a product is technically superior or offers advanced features, its perceived value by customers ultimately determines the optimal price point. Aligning pricing with customer perceptions of value helps maximize revenue and profitability for both transaction participants. The authors’ method enables the determination of the boundaries of the market price range for an innovation with sufficient accuracy. Combining traditional pricing methods with price sensitivity analysis of industrial customers can offer several advantages, leveraging the strengths of each approach to improve the price-determining process for industrial “technology-push” innovations.