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Given that AI is becoming an increasingly active participant in work teams, this study explores how team trust emerges in human–AI teams compared to human–human teams. Adopting a multi‐level approach, we conducted two experimental studies (NStudy1 = 247 two‐member teams and NStudy2 = 106 three‐member teams, 828 individuals overall) and investigated how team composition (with AI or human team members) impacts interpersonal trust (affective and cognitive) and thus team trust. In two‐member teams, interpersonal trust via perceived trustworthiness and not via perceived similarity was lower in human–AI teams compared to human–human teams. Exploratory findings showed that team identification and cognitive interpersonal trust were also lower in two‐member human–AI teams than in human–human teams. However, in three‐member teams, we found no differences in team trust via interpersonal trust between the two team types. Instead, our findings revealed that perceived trustworthiness and perceived similarity increased interpersonal trust and, in turn, team trust for both team types. With this research, we showed that underlying theories and evidence of team trust in human‐only teams can enhance understanding of human–AI teams, though the results indicated certain differences that call for further investigation. [ABSTRACT FROM AUTHOR]

The following article is devoted to studying the problem of evaluating employee performance in a team. The factors and conditions that affect the effectiveness of teamwork in an organisation, as well as the advantages of its application are studied. Approaches to assessing teamwork effectiveness have been systematized and key performance indicators have been established. It has been proved that, in modern organizations, employee remuneration for efficient work is a vector that encourages the team to achieve high results. An approach to managing teamwork effectiveness based on the assessment of key performance indicators of its members with the aim of determining additional remuneration is proposed.

This study presents a multidisciplinary end-to-end design, build, and test drive experience of a Formula Society of Automatic Engineers (FSAE) electric vehicle. The design team members’ background include computer engineering, electrical engineering, and mechanical engineering expertise. Each team member worked on a sub-team namely mechanical, drivetrain, supervisory control and data acquisition (SCADA), and battery management system (BMS). The mechanical team modified/redesigned a gasoline FSAE car frame to accommodate the battery pack, cooling systems, electric drive train, and SCADA hardware. The drivetrain team designed a combinational logic-based tractive system control board to enhance the safety and reliability of the drivetrain. The SCADA team used a model-view-controller software architecture and agile development practices to design and implement a custom electric vehicle operating system and the main brain hardware. The BMS team designed the sensing network and communication protocol to provide an update on the state of the health of the energy source. A thorough description of each sub-system is provided herein. System integration and field test results are also included.

This study presents a multidisciplinary end-to-end design, build, and test drive experience of a Formula Society of Automatic Engineers (FSAE) electric vehicle. The design team members' background include computer engineering, electrical engineering, and mechanical engineering expertise. Each team member worked on a sub-team namely mechanical, drivetrain, supervisory control and data acquisition (SCADA), and battery management system (BMS). The mechanical team modified/redesigned a gasoline FSAE car frame to accommodate the battery pack, cooling systems, electric drive train, and SCADA hardware. The drivetrain team designed a combinational logic-based tractive system control board to enhance the safety and reliability of the drivetrain. The SCADA team used a model-view-controller software architecture and agile development practices to design and implement a custom electric vehicle operating system and the main brain hardware. The BMS team designed the sensing network and communication protocol to provide an update on the state of the health of the energy source. A thorough description of each sub-system is provided herein. System integration and field test results are also included. [ABSTRACT FROM AUTHOR]

The following article is devoted to studying the problem of evaluating employee performance in a team. The factors and conditions that affect the effectiveness of teamwork in an organisation, as well as the advantages of its application are studied. Approaches to assessing teamwork effectiveness have been systematized and key performance indicators have been established. It has been proved that, in modern organizations, employee remuneration for efficient work is a vector that encourages the team to achieve high results. An approach to managing teamwork effectiveness based on the assessment of key performance indicators of its members with the aim of determining additional remuneration is proposed. [ABSTRACT FROM AUTHOR]