This research investigates the factors influencing the capital structure of 271 non-financial firms listed on the Korean Stock Exchange (KSE) over a broad period from 1995 to 2021, encompassing both stable and crisis conditions. Employing a dynamic panel data model and the generalized method of moments (GMM) estimation, we address the endogeneity issue introduced by the inclusion of lagged dependent variables. Our research integrates firm-specific internal factors with macroeconomic external variables to provide a comprehensive understanding of the influence of varying economic environments on capital structure. Our study suggests that in times of economic stability, the capital structure decisions of a firm are more influenced by internal factors such as profitability. However, in periods of economic downturns, it is the external macroeconomic market conditions that tend to have a greater impact on these decisions. It is also noteworthy that both book leverage (BL) and market leverage (ML) exhibit quicker adjustments during stable periods as opposed to periods of crisis. This indicates a higher agility of firms in adapting their capital structures in stable, normal conditions. Our findings contribute to the existing literature by offering a holistic view of capital structure determinants in Korean firms. They underscore the necessity of adaptable financial strategies that account for both internal dynamics and external economic conditions. This study fills a gap in current research, presenting new insights into the dynamics of capital structure in Korean firms and suggesting a multifaceted approach to understanding capital structure in diverse economic contexts.
Efficiency of city logistics activities suffers due to conflicting personal preferences and distributed decision making by multiple city logistics stakeholders. This is exacerbated by interdependency of city logistics activities, decision making with limited information and stakeholders’ preference for personal objectives over system efficiency. Accordingly, the key to understanding the causes of inefficiency in the city logistics domain is understanding the interaction between heterogeneous stakeholders of the system. With the capabilities of representing a system in a natural and flexible way, agent based modelling (ABM) is a promising alternative for the city logistics domain. This research focuses on developing a framework for the successful implementation of the ABM approach for the city logistics domain. The framework includes various elements – a multi-perspective semantic data model (i.e. ontology) and its validation, the development of an agent base model using this ontology, and a validation approach for the agent-based model. Conclusively, the framework shows that a rigorous course can be taken to successfully implement agent based modelling approach for the city logistics domain.
