Journal of Business and Innovation (Бизнес & Инноваци)

APPLICATION OF MULTI-OBJECTIVE OPTIMIZATION IN AN OLIGOPOLY MARKET

Enkhbat Rentsen — 2026-02-10

Modeling competitive behavior in oligopolistic markets through multiobjective optimization is closely linked to decision-making processes in economic systems. This study proposes an approach for identifying Pareto-optimal solutions using empirical export data of coking coal from Mongolia, Russia, and Australia. The Pareto-efficient equilibrium was obtained by transforming the multi-objective problem into a global optimization problem using the weighted sum scalarization technique based on Theorem 2 and solving it in MATLAB. Two experimental models were constructed using different price–cost function structures. The numerical results indicate that the optimal export quantities of the three countries are highly dependent on the functional form of the price–cost relationship. When the price function exhibits quadratic growth, equilibrium supply levels shift toward higher values. These findings demonstrate the significant influence of price elasticity and cost structure on strategic decision-making in resource-based oligopoly markets. The results may provide useful insights for developing optimal export strategies in markets with oligopolistic characteristics.

A NEW PARADIGM OF BIG DATA–BASED RISK ASSESSMENT: EVIDENCE FROM A METAL MINING COMPANY

Tsolmon Sodnomdavaa — 2026-02-10

In recent years, mining companies have been increasingly exposed to a wide range of environmental, social, economic, and technological risks, which have adversely affected operational sustainability. Conventional risk assessment approaches have limited capacity to incorporate real-time data and to adapt to dynamic operating conditions. In contrast, artificial intelligence and machine learning methods offer new opportunities to address these shortcomings. This study applies GRU, BiLSTM, XGBoost, and Random Forest models to three primary data sources: a copper price series covering 1960 to 2024, more than 700,000 hours of industrial process data, and over 188,000 recorded occupational accident cases. Overall, the findings demonstrate that AI and ML-based approaches can transform mining risk management from a reactive framework into a proactive, real-time, and data-driven integrated system.

ANALYZING THE ECONOMIC ENVIRONMENT USING MACHINE LEARNING

Dulguuntuya Bataa — 2026-02-10

Studying and evaluating a country’s trade and business environment ensures economic stability and enhances organizational competitiveness. Business environment assessments serve as a foundation for identifying entrepreneurs’ challenges and determining future development directions. This research aimed to apply machine learning techniques to classify the economic environment data that received the lowest evaluation in the 2020 joint study conducted by the Mongolian National Chamber of Commerce and Industry and the Business School. The study employed machine learning methods, including K-Means clustering, Principal Component Analysis (PCA), and Decision Tree algorithms.

THE CURRENT STATE OF THE VISUAL ARTS MARKET AND CONCEPTUAL MAPPING OF THE CREATIVE VALUE CHAIN IN THE VISUAL ARTS SECTOR

Baasanjargal Purev — 2026-02-10

In recent years, developed and rapidly emerging economies have increasingly embraced the principles of a knowledge-based economy and sustainable development, positioning the creative industries as a strategic pathway for long-term growth. Globally, the contribution of the creative sector to socio-economic development continues to rise, with projections indicating that it will account for 10% of global GDP by 2030. Within this context, the visual arts represent a core subsector of the creative industries, comprising approximately 11% of the global Cultural and Creative Industries (CCI) market. In Mongolia, while numerous studies have examined visual arts through the lenses of art history, archaeology, ethnography, and cultural studies, research adopting a market-oriented and marketing perspective remains scarce, and no comprehensive analysis encompassing all market stakeholders has been conducted. Therefore, this study aims to assess the current state of the visual arts market in Mongolia and to develop a conceptual mapping of the creative value chain within the sector.

THE IMPACT OF BEHAVIORAL FACTORS ON STOCK PRICES

Bayansan Purev — 2026-02-10

This study examines the impact of behavioral factors on stock prices in the Mongolian Stock Exchange using empirical models based on behavioral finance theory. Monthly data from 2019 to 2025 were analyzed using CSAD, CSSD, and AR(1) GLS regression models. The results indicate that herding behaviors and loss aversion bias significantly reduce price volatility under certain market conditions. Conversely, overconfidence bias was found to increase volatility during bullish markets. Sectoral differences in behavioral patterns were evident, with stronger effects observed in food, finance, and light industry sectors, highlighting the theoretical and practical importance of integrating behavioral factors into investment decisions and risk management.

A STUDY ON FACTORS INFLUENCING THE DECISION MAKING BEHAVIOR IN PURCHASING VEHICLE INSURANCE SERVICES

Sugarjav Batsaikhan — 2026-02-10

Despite the experienced significant growth of the insurance sector in Mongolia, particularly in motor vehicle insurance, there remains a paucity of comprehensive research examining the key factors influencing consumers’ (drivers and vehicle owners) purchase intentions in selecting and purchasing insurance services, as well as the interrelationships among these factors. This study aims to identify the determinants affecting consumers’ decision-making regarding motor vehicle insurance purchases. A total of 340 respondents participated in the study, and six hypotheses were tested using SPSS 27.0. The results indicate that an insurance company’s reputation, consumer trust, and advertising exert a positive influence on consumers’ purchase intentions. Conversely, the hypothesized positive effects of compensation processing time, ease of obtaining insurance, and perceived insurance benefits on purchase intention were not supported. These findings provide valuable insights for insurers seeking to enhance consumer engagement and inform strategic marketing decisions in the Mongolian insurance market.

STUDY OF FACTORS AFFECTING CONSUMER PURCHASE INTENTIONS FOR OVER-THE-TOP SERVICES

Anudari Yadamsuren — 2026-02-10

In recent years, Over-the-Top (OTT) services have become widely used, increasingly replacing traditional television and cable services. This study aims to identify the factors influencing Mongolian consumers’ intention to use OTT services based on the Technology Acceptance Model (TAM). A total of 372 respondents aged 16 and above residing in Ulaanbaatar participated in the survey. Data were analyzed using SPSS, including reliability testing, factor analysis, and regression analysis. The results indicate that content quality, entertainment, perceived value, and electronic word-of-mouth (e-WOM) have a significant positive influence on consumers’ intention to use OTT services. However, the core TAM variables—perceived ease of use and perceived usefulness—did not show statistically significant effects.

A STUDY ON THE IMPACT OF BUSINESS ANALYTICS ON DECISION-MAKING BASED ON ONLINE COMMERCE CUSTOMER ORDER DATA

Iderbat Togtokhbayar — 2026-02-10

The purpose of this study is to evaluate the impact of business analytics methodologies on the quality of managerial decision-making, based on real online commerce data from Company A for the year 2024. The study utilizes a total of 98,432 order records and includes key variables such as district, sub-district (khoroo), order amount, discounts, promotions, and customer purchase frequency.
In Power BI, an interactive dashboard was developed to visualize the organization’s sales performance, discount and promotion policies, regional differences, and seasonal fluctuations. In SPSS, the research hypotheses were tested and validated using correlation, regression, and ANOVA analyses. The results indicate that discount and promotion policies have a statistically significant positive relationship with sales performance.

TRADITIONAL VERSUS CYBER WORKPLACE BULLYING: MECHANISMS LEADING TO EMPLOYEE BURNOUT

Altantsetseg Battulga — 2026-02-10

Workplace bullying is a common psychosocial stressor in modern organizational settings, significantly undermining employee well-being, job performance, and overall organizational effectiveness. In-person bullying typically involves frequent, negative behaviors from colleagues or supervisors, such as neglect, belittlement, and verbal abuse, whereas cyberbullying occurs through digital communication channels, targeting employees’ reputation, personal space, and social interactions. This study investigates the direct effects of both in-person and cyberbullying on employee disengagement using data from 150 employees in Mongolian business organizations. Results indicate that both forms of bullying increase psychological exhaustion, thereby intensifying disengagement. These findings offer theoretically informed guidance for organizational practice, emphasizing the need to detect and prevent workplace bullying and to implement policies that protect employees’ psychological well-being.