## 2 Background and Literature Review
### Benchmarking Methods  
Benchmarking is imperative for standardizing HMT performance, however, there are very limited relevant information in the literature regarding it. There are several benchmarking methods that have been developed to assess team efficacy with team members as either machines or humans but not as both together. The most obvious field of benchmarking is seen in human teaming at the industry level. Many companies practice different benchmarking methods to analyze and evaluate operational performance of an organization with a specific mission, the most pronounced of which is known as matrix benchmarking. Matrix Benchmarking helps in finding lapses in delivery of task execution and indicates areas that require potential improvements. To perform benchmarking of companies, it is important to utilize a generalized categorization approach. The two key variables of a generalized categorization are called cost categories and cost levers [39]. Here, the cost categories are further divided into three parts: payroll, capital, and material, whereas cost levers are divided into four parts: production, volume, factor costs, and efficiency. Moreover, these two variables are also utilized to quantify the cost difference between a company's product and its competitors. The office of personnel management interagency advisory group (IAG) has devised four benchmarking models to evaluate a team performance, as follows [40]. 1. Individual team member assessment in a team: In this model, the team member's individual performance is evaluated in a way unrelated to the team objectives. The performance variables of individuals include task complexity, task success, and team member efficacy. The elements of team performance are not considered in this model. 2. Team member contribution to a team setting: Here, the team member's overall performance variables, as well as a team member's contribution to at least one element of the team's mission, are the subject of performance evaluation. In this model, the performance evaluation is conducted from the perspective of individual team member efficacy, while team productivity is not evaluated. 3. Group performance: In this model, the focus is given to performance variables of both the team and individual members. There is at least one element of team group performance related to an individual member in the evaluation process. 4. Group performance (No individual appraisal): The performance is determined at team level, and no individual member appraisal methods are conducted in the due process. This gives insight on overall team productivity when assigned a task. However, the benchmarking methods at the HMT level require a different set of factors, and to date, no standardization has been proposed. Some of the factors that govern the effectiveness of HMT are discussed in [41]. In fact, there are numerous factors that will determine the extent to which HMT will achieve the desired level of effectiveness when employed. These factors are based on previous research on HMI design and on human-human team performance. Some of the factors that have been discussed in the literature are:  
* Automation transparency: The operator must perceive the automation agent's intent and reasoning and be able to elicit additional factors based on the mission objective. In fact, detecting and understanding the status of human team members may be one of the more challenging aspects of autonomous-agent design in HMT. * Two-way communication: Communications between humans and machines are necessary for establishing and maintaining a common knowledge of task goals, exchanging information, and reporting errors. The advent of natural-language processing incorporated into machines has enhanced communication that matches human capabilities. It is a crucial factor for effective human-autonomy collaborations in pursuit of a common goal. * Workload: This factor has a direct influence on task execution and team performance.