Always fair, encouraging, and motivating.
Inspires confidence and independent thinking.
Inspires curiosity and a thirst for knowledge.
A true expert who inspires confidence.
Inspires students to achieve their best.
Stanislav Stakhovych is a Senior Lecturer in the Department of Marketing at Monash Business School, Monash University, based at the Caulfield campus. He obtained his PhD in 2010 from the University of Groningen, The Netherlands. His research interests include marketing models building, multivariate data analysis, marketing dynamics, marketing strategy, spatial modelling, and Bayesian econometrics. Areas of expertise encompass customer base analysis, Bayesian methods, marketing dynamics, e-commerce, marketing analytics, services marketing, online retailing, Bayesian modeling in marketing, geospatial marketing, and mobile marketing. Stakhovych joined Monash University in July 2010 and has contributed to the academic community through teaching and supervision. He serves as chief examiner for several units in the Faculty of Business and Economics, including MKF5912 Marketing research, MKF2131 Marketing decision analysis, and MKF2540 Retail management principles. He has supervised PhD theses, such as 'An Empirical Study of the Influence of Online Review Content on Consumer Decisions' in 2023.
Stakhovych has published in prominent journals, with eight research outputs on his Monash profile, including seven journal articles and one conference paper. Key publications are 'Empirical decomposition of customer responses to discount coupons in online FMCG retailing' (Journal of Retailing and Consumer Services, 2021, with Montazeri, Tamaddoni, Ewing), 'Mix&Match: a resource-based complaint recovery framework for tangible compensation' (Journal of Service Research, 2020, with Tamaddoni), 'The impact of personalised incentives on the profitability of customer retention campaigns' (Journal of Marketing Management, 2017, with Tamaddoni, Ewing), 'Comparing churn prediction techniques and assessing their performance: a contingent perspective' (Journal of Service Research, 2016, with Tamaddoni, Ewing), 'Customer Churn Models: A Comparison of Probability and Data Mining Approaches' (2016), 'Managing B2B customer churn, retention and profitability' (Industrial Marketing Management, 2014, with Tamaddoni Jahromi, Ewing), 'Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values' (2012), 'Specification of spatial models: a simulation study on weights matrices' (2009), and 'Cross-shareholding in the Japanese Banking Sector, Tacit Collusion, and Market Power' (2009). His work addresses customer retention, churn prediction, personalized incentives, complaint recovery, and spatial modeling in marketing contexts.