The advent of globalized trade has led to unprecedented growth in the volume and complexity of maritime logistics. As one of the most cost-effective modes of transportation, maritime shipping has become indispensable for connecting economies and supporting international trade. However, this growth comes with substantial environmental and operational challenges. The sector's heavy reliance on fossil fuels contributes significantly to global greenhouse gas (GHG) emissions, accounting for nearly 2.89% of global emissions Smith et al. [2014], [IMO]. Moreover, the International Maritime Organization (IMO) has outlined a strategy to reduce GHG emissions from international shipping by at least 50% by 2050 compared to 2008 levels, aiming for eventual decarbonization [IMO]. These ambitious targets underscore the pressing need for transformative solutions to meet regulatory requirements and societal expectations. Environmental pressures are further compounded by the intricate logistics of coordinating diverse stakeholders, including shipping companies, port authorities, and policymakers, each with unique objectives and constraints.

In a complex adaptive system, diverse agents perform various actions without adherence to a predefined structure. The achievement of joint actions will be a result of continual interactions among them that shape a dynamic network. Agents may form an ad hoc organization based on dynamic network of interactions for the purpose of achieving a long term objective, which is called a Network Organization (NO). For the dominant influences of the network substrate in an NO, multiple effects of it have an impact on the NO behaviors and directions. We envisioned several dimensions of such effects to be synergy, social capital, externality, influence, etc. The focus of this paper is on measuring synergy as one of those possible network effects. Synergy describes different modalities of compatibility among agents when performing a set of coherent and correspondingly different actions. When agents are under no structural obligation to contribute, synergy is quantified through multiple forms of serendipitous agent chosen benevolence among them. The approach of this paper is to measure four types of benevolence and the pursuant synergies from them stemming from agent interactions. We exemplify this approach using a case study of a multiplayer online game.

The NO paradigm can model many operations. Examples When agents dwell inside an organization, they form patterns are systems of river dam control, factory cells, electrical of interactions that we call paradigms. There are many power grids, and traffic control on land, sea, and space. As existing paradigms to describe organizations, which affect a paradigm, it does not functionally alter the operations to its performance features. These paradigms include hierarchies, which it is applied. The paradigm can be understood in terms holarchies, coalitions, teams, congregations, societies, of the ways it permits command and control regimes. Invariably, federations, markets and matrix organizations (Horling and NO relies on a network on which it dwells.