Small and medium-sized enterprises (SMEs) in the food and beverage industry play an important role in advancing economic, social and environmental sustainability in emerging economies. However, many resource-endowed SMEs remain unable to translate their potential into sustainable business outcomes. This study examines the factors influencing the business sustainability of food and beverage SMEs in Northeastern Thailand and explains how organizational capabilities are hierarchically structured to create sustainable competitive advantage. A mixed-methods design was employed. Qualitative in-depth interviews with entrepreneurship-incubation experts informed the development of the research instrument, while quantitative data were collected from 401 entrepreneurs in the three highest-GPP provinces: Nakhon Ratchasima, Khon Kaen and Ubon Ratchathani. Structural equation modelling was used to test causal relationships among strategic planning, finance and accounting, leadership, business knowledge, product development and external factors. The model demonstrated acceptable fit and explained 92% of the variance in business sustainability. Strategic planning emerged as the strongest direct driver, supported by business knowledge and product development as complementary capabilities. In contrast, finance, leadership and external factors showed no significant direct effects, suggesting indirect or contextual roles. The study proposes a Planning-Centric Sustainability Model and contributes to Resource-Based View and Dynamic Capabilities perspectives in emerging economies.

This article aims to present the state of the art of applying machine learning to business operations. The objective of the article is to review related research articles both domestically and internationally from 2019-2024 (5 years). In the current Machine Learning is becoming very popular. The rapid growth and transformative potential across multiple domains are due to relentless advancements in technology that are continually evolving and adaptable across diverse sectors. In particular, industries and businesses that are the main economic drivers of Thailand are beginning to recognize the importance and are increasingly applying various aspects of machine learning (ML) for business development. This includes customer data analysis, sales forecasting, demand forecasting, customer service improvement, and market data analysis. This research article will compare the characteristics, advantages and disadvantages of each type of machine learning, as well as the application of each type of machine learning in various dimensions of business. As technology continues to grow, it will impact the ability to drive innovation and increase efficiency, leading to processes that enhance business capabilities and benefits that will change business in a positive direction and respond to future national policies.

Small- and medium-sized enterprises (SMEs) in the food and beverage industry play an important role in advancing business sustainability in emerging economies. However, many resource-endowed SMEs remain unable to translate their potential into sustainable business outcomes. This study examines the factors influencing the business sustainability of food and beverage SMEs in Northeastern Thailand and explains how organizational capabilities are hierarchically structured to create sustainable competitive advantage. A mixed-methods design was employed. Qualitative in-depth interviews with entrepreneurship-incubation experts and entrepreneurs revealed that SME sustainability problems were closely associated with weak planning practices, limited market knowledge, informal financial systems, and insufficient product development capability. These insights informed the development of the research instrument. Quantitative data were then collected from 401 entrepreneurs in the three highest-GPP provinces: Nakhon Ratchasima, Khon Kaen, and Ubon Ratchathani. Structural equation modelling was used to test causal relationships among strategic planning, finance and accounting, leadership, business knowledge, product development, external factors, and business sustainability. The model demonstrated acceptable fit and explained 92% of the variance in business sustainability. Strategic planning emerged as the strongest direct driver, supported by business knowledge and product development as complementary capabilities. Finance, leadership, and external factors showed no significant direct effects. The study proposes a Planning-Centric Sustainability Model and contributes to Resource-Based View, Competency-Based View, and Dynamic Capabilities perspectives in emerging economies.