Energies 2015,8 11007 studies [121-123]show that ignoring the effects of social networks can change occupants'energy-saving behaviors into bad behaviors. In addition to the effects of social structures,the variability of individual occupants'energy intensity (e.g.,kWh/ft2/occupant/year)over time can also influence the success of intervention techniques [12,104]. Studies indicate that low variability in energy intensity demonstrate that an occupant has strong energy habits.Therefore,interventions seeking to influence such rigid occupants are much harder to accomplish than interventions targeting occupants with flexible habits [12,99,101,122,123].Furthermore,in addition to rigid occupants,extremists can affect the performance of occupancy-intervention tools.Such occupants significantly affect their peers'opinions and therefore cloud the interventions'performance;even a small number of extremists could push their ideas onto a large number of occupants within a built environment [79,124-127].Finding the number of extremists and studying how they may interrupt an intervention study can help researchers reduce such occupants'effects on occupancy-intervention techniques.Since organizational network and structure dynamics affect the occupants'communication within commercial buildings,studying the extremists'effects within different structures/networks could also help researchers understand how extremists influence overall energy consumption. With these categories and concerns in mind,occupancy-focused intervention efforts in commercial sectors mainly focused on occupancy interactions and feedback techniques,described below. 4.1.Occupancy Interactions Occupant behaviors are significantly influenced by peers in their built environment,especially when there are strong relationship ties among occupants.Peer pressure capitalizes on the fact that occupants influenced by interventions interact with other occupants to influence them to improve their energy-use behaviors [105,128-131].In one case,an occupant could observe and adjust his or her own behavior to follow other occupants'energy-saving behaviors.In fact,peer pressure interactions engage occupants to help themselves.Azar and Menassa [12,87]modeled peer pressure interactions among occupants. Each occupant sent a message to other occupants,and the interaction occurred when the two occupants' energy-use characteristics paralleled each other.In fact,Azar and Menassa assumed that peer pressure is most effective when the energy-use characteristics of the two occupants are the same and is least effective otherwise.They employed their experiment on a case study of medium office buildings and achieved up to 24.7 percent energy-savings through peer-pressure intervention.However,the mentioned main assumption of these works could limit the achieved conclusions.For example,an extremist could significantly affect his/her peers-even those who have energy-saving behavior-and therefore, two occupants with different energy-behavior characteristics could significantly affect each other's behavior.Carrico and Riemer [132]also studied the effect of peer pressure during a case study of office buildings for a four-month period of time.In their study,they disseminated energy-saving information among occupants,and considered that each occupant would educate and encourage others to have energy-saving behaviors.Their results indicated a 4 percent reduction in total energy use.However,they did not clearly discuss how peer pressure affects occupants'behavior.Since the peer-pressure concept involves different kinds of interactions among occupants,such research might significantly discuss which kind of peer-pressure interaction influenced occupants'energy behavior.Energies 2015, 8 11007 studies [121–123] show that ignoring the effects of social networks can change occupants’ energy-saving behaviors into bad behaviors. In addition to the effects of social structures, the variability of individual occupants’ energy intensity (e.g., kWh/ft2 /occupant/year) over time can also influence the success of intervention techniques [12,104]. Studies indicate that low variability in energy intensity demonstrate that an occupant has strong energy habits. Therefore, interventions seeking to influence such rigid occupants are much harder to accomplish than interventions targeting occupants with flexible habits [12,99,101,122,123]. Furthermore, in addition to rigid occupants, extremists can affect the performance of occupancy-intervention tools. Such occupants significantly affect their peers’ opinions and therefore cloud the interventions’ performance; even a small number of extremists could push their ideas onto a large number of occupants within a built environment [79,124–127]. Finding the number of extremists and studying how they may interrupt an intervention study can help researchers reduce such occupants’ effects on occupancy-intervention techniques. Since organizational network and structure dynamics affect the occupants’ communication within commercial buildings, studying the extremists’ effects within different structures/networks could also help researchers understand how extremists influence overall energy consumption. With these categories and concerns in mind, occupancy-focused intervention efforts in commercial sectors mainly focused on occupancy interactions and feedback techniques, described below. 4.1. Occupancy Interactions Occupant behaviors are significantly influenced by peers in their built environment, especially when there are strong relationship ties among occupants. Peer pressure capitalizes on the fact that occupants influenced by interventions interact with other occupants to influence them to improve their energy-use behaviors [105,128–131]. In one case, an occupant could observe and adjust his or her own behavior to follow other occupants’ energy-saving behaviors. In fact, peer pressure interactions engage occupants to help themselves. Azar and Menassa [12,87] modeled peer pressure interactions among occupants. Each occupant sent a message to other occupants, and the interaction occurred when the two occupants’ energy-use characteristics paralleled each other. In fact, Azar and Menassa assumed that peer pressure is most effective when the energy-use characteristics of the two occupants are the same and is least effective otherwise. They employed their experiment on a case study of medium office buildings and achieved up to 24.7 percent energy-savings through peer-pressure intervention. However, the mentioned main assumption of these works could limit the achieved conclusions. For example, an extremist could significantly affect his/her peers—even those who have energy-saving behavior—and therefore, two occupants with different energy-behavior characteristics could significantly affect each other’s behavior. Carrico and Riemer [132] also studied the effect of peer pressure during a case study of office buildings for a four-month period of time. In their study, they disseminated energy-saving information among occupants, and considered that each occupant would educate and encourage others to have energy-saving behaviors. Their results indicated a 4 percent reduction in total energy use. However, they did not clearly discuss how peer pressure affects occupants’ behavior. Since the peer-pressure concept involves different kinds of interactions among occupants, such research might significantly discuss which kind of peer-pressure interaction influenced occupants’ energy behavior