Common use of Case Study Analysis Clause in Contracts

Case Study Analysis. Dependent variable Data was collected about OSH hazards and the risk control solutions implemented within the case examples. This data was elicited during the interviews and supplemented with site-based observations and examination of project documentation (e.g. plans and drawings). For each feature of work, a score was generated reflecting the quality of implemented risk control solutions. This score was based on the hierarchy of control (HOC). The Hierarchy of Control classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control The hierarchy of control (HOC) is a well-established framework in OSH (see, for example, Xxxxxxx, 2006). The HOC classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control. At the top of the HOC is the elimination of a hazard/risk altogether. This is the most effective form of control because the physical removal of the hazard/risk from the work environment means that workers are not exposed to it. The second level of control is substitution. This involves replacing something that produces a hazard with something less hazardous. At the third level in the HOC are engineering controls, which isolate people from hazards. The top three levels of control (i.e, elimination, substitution and engineering) are technological because they act on changing the physical work environment. Beneath the technological controls, level four controls are administrative in nature, such as developing safe work procedures or implementing a job rotation scheme to limit exposure. At the bottom of the hierarchy at level five is personal protective equipment (PPE) – the lowest form of control. Although, much emphasized and visible on a worksite, at best, PPE should be seen as a “last resort,” see, for example Xxxxxxxx et al.’s analysis of barriers to the use of eye protection (Xxxxxxxx et al. 2009). The bottom two levels in the HOC represent behavioral controls that they seek to change the way people work (for a summary of the limitations of these controls see Xxxxxxx, 2006). Each level of the HOC was given a rating ranging from one (personal protective equipment) to five (elimination). The risk controls implemented for hazards/risks presented by each feature of work were assigned a score on this five point scale. In the event that no risk controls were implemented, a value of zero was assigned. Independent variable Social network analysis (SNA) was used to map the social relations between participants involved in making design decisions about each feature of work. SNA is an analytical tool to study the exchange of resources between participants in a social network. Using social network analysis, patterns of social relations can be represented in the form of visual models (known as sociograms) and described in terms of quantifiable indicators of network attributes. In a sociogram, participants are represented as nodes. To varying extents, these nodes are connected by links which represent the relationships between participants in the network. SNA has been recommended as a useful method for understanding and quantifying the roles and relationships between construction project participants (Xxxxx, 2004; Xxxxxxxxx et al. 2008). The technique has been used to analyse knowledge flows between professional contributors to project decision-making (see, for example, Xxxx et al. 2012; Xxxxx et al. 2013). Network characteristics have also been used to explain failures in team-based design tasks (Xxxxxxxxx et al. 2008) and identify barriers to collaboration that arise as a result of functional or geographic segregation in construction organizations (Xxxxxxxxx et al. 2010). More recently, Xxxxxxxxxx et al. (2013) used SNA to investigate the relationship between safety communication patterns and OSH performance in construction work crews. In order to gauge the construction contractor’s prominence in a project social network, the contractor’s degree centrality was calculated. Degree centrality refers to the extent to which one participant is connected to other participants in a network. Thus, degree centrality is the ratio of the number of relationships the actor has relative to the maximum possible number of relationships that the network participant could have. If a network participant possesses high degree centrality then they are highly involved in communication within the network relative to others. Xxxxx (2005) argues that degree centrality is a useful indicator of power and influence within a network. Degree centrality can be measured by combining the number of lines of communication into and out of a node in the network (see, for example, Alsamadani et al., 2013). This presents an aggregate value representing the participant’s communication activity. However, the independent variable used in this research was calculated using only the construction contractors’ outgoing communication. This was a deliberate choice because the research aim was to investigate whether OSH risk control is of a higher quality when project decisions are made with due consideration of construction process knowledge. Thus, the flow of communication from the construction contractor to other network members was deemed to be of greater relevance that the volume of information they received. From: Xxxxxxxxx, X., Xxxxxxx, X., Xxxxxxx, N., Xxxxxxxx, P., Xxxxxxx, B., Xxxxx, X., XxXxx, X. & Xxxxxxxx, X. (2014). ‘Construction Hazard Prevention: The Need to Integrate Process Knowledge into Product Design’. Paper presented at the CIB W099 International Conference: Achieving Sustainable Construction Health and Safety, 2-3 June 2014 Lund, Sweden.

Case Study Analysis. Dependent variable Data was collected about OSH hazards and the risk control solutions implemented within the case examples. This data was elicited during the interviews and supplemented with site-based observations and examination of project documentation (e.g. plans and drawings). For each feature of work, a score was generated reflecting the quality of implemented risk control solutions. This score was based on the hierarchy of control (HOC). The Hierarchy of Control classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control The hierarchy of control (HOC) is a well-established framework in OSH (see, for example, Xxxxxxx, 2006). The HOC classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control. At the top of the HOC is the elimination of a hazard/risk altogether. This is the most effective form of control because the physical removal of the hazard/risk from the work environment means that workers are not exposed to it. The second level of control is substitution. This involves replacing something that produces a hazard with something less hazardous. At the third level in the HOC are engineering controls, which isolate people from hazards. The top three levels of control (i.e, elimination, substitution and engineering) are technological because they act on changing the physical work environment. Beneath the technological controls, level four controls are administrative in nature, such as developing safe work procedures or implementing a job rotation scheme to limit exposure. At the bottom of the hierarchy at level five is personal protective equipment (PPE) – the lowest form of control. Although, much emphasized and visible on a worksite, at best, PPE should be seen as a “last resort,” see, for example Xxxxxxxx et al.’s analysis of barriers to the use of eye protection (Xxxxxxxx et al. 2009). The bottom two levels in the HOC represent behavioral controls that they seek to change the way people work (for a summary of the limitations of these controls see Xxxxxxx, 2006). Each level of the HOC was given a rating ranging from one (personal protective equipment) to five (elimination). The risk controls implemented for hazards/risks presented by each feature of work were assigned a score on this five point scale. In the event that no risk controls were implemented, a value of zero was assigned. Independent variable Social network analysis (SNA) was used to map the social relations between participants involved in making design decisions about each feature of work. SNA is an analytical tool to study the exchange of resources between participants in a social network. Using social network analysis, patterns of social relations can be represented in the form of visual models (known as sociograms) and described in terms of quantifiable indicators of network attributes. In a sociogram, participants are represented as nodes. To varying extents, these nodes are connected by links which represent the relationships between participants in the network. SNA has been recommended as a useful method for understanding and quantifying the roles and relationships between construction project participants (XxxxxPryke, 2004; Xxxxxxxxx et al. 2008). The technique has been used to analyse knowledge flows between professional contributors to project decision-making (see, for example, Xxxx Ruan et al. 2012; Xxxxx Zhang et al. 2013). Network characteristics have also been used to explain failures in team-based design tasks (Xxxxxxxxx et al. 2008) and identify barriers to collaboration that arise as a result of functional or geographic segregation in construction organizations (Xxxxxxxxx et al. 2010). More recently, Xxxxxxxxxx Alsamadani et al. (2013) used SNA to investigate the relationship between safety communication patterns and OSH performance in construction work crews. In order to gauge the construction contractor’s prominence in a project social network, the contractor’s degree centrality was calculated. Degree centrality refers to the extent to which one participant is connected to other participants in a network. Thus, degree centrality is the ratio of the number of relationships the actor has relative to the maximum possible number of relationships that the network participant could have. If a network participant possesses high degree centrality then they are highly involved in communication within the network relative to others. Xxxxx Pryke (2005) argues that degree centrality is a useful indicator of power and influence within a network. Degree centrality can be measured by combining the number of lines of communication into and out of a node in the network (see, for example, Alsamadani et al., 2013). This presents an aggregate value representing the participant’s communication activity. However, the independent variable used in this research was calculated using only the construction contractors’ outgoing communication. This was a deliberate choice because the research aim was to investigate whether OSH risk control is of a higher quality when project decisions are made with due consideration of construction process knowledge. Thus, the flow of communication from the construction contractor to other network members was deemed to be of greater relevance that the volume of information they received. From: XxxxxxxxxWakefield, X.R., Xxxxxxx, X.H., Xxxxxxx, N., Xxxxxxxx, P., Xxxxxxx, B., Xxxxx, X.T., XxXxx, X. A. & Xxxxxxxx, X. L. (2014). ‘Construction Hazard Prevention: The Need to Integrate Process Knowledge into Product Design’. Paper presented at the CIB W099 International Conference: Achieving Sustainable Construction Health and Safety, 2-3 June 2014 Lund, Sweden.

Case Study Analysis. Dependent variable Data was collected about OSH hazards and the risk control solutions implemented within the case examples. This data was elicited during the interviews and supplemented with site-based observations and examination of project documentation (e.g. plans and drawings). For each feature of work, a score was generated reflecting the quality of implemented risk control solutions. This score was based on the hierarchy of control (HOC). The Hierarchy of Control classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control The hierarchy of control (HOC) is a well-established framework in OSH (see, for example, Xxxxxxx, 2006). The HOC classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control. At the top of the HOC is the elimination of a hazard/risk altogether. This is the most effective form of control because the physical removal of the hazard/risk from the work environment means that workers are not exposed to it. The second level of control is substitution. This involves replacing something that produces a hazard with something less hazardous. At the third level in the HOC are engineering controls, which isolate people from hazards. The top three levels of control (i.e, elimination, substitution and engineering) are technological because they act on changing the physical work environment. Beneath the technological controls, level four controls are administrative in nature, such as developing safe work procedures or implementing a job rotation scheme to limit exposure. At the bottom of the hierarchy at level five is personal protective equipment (PPE) – the lowest form of control. Although, much emphasized and visible on a worksite, at best, PPE should be seen as a “last resort,” see, for example Xxxxxxxx et al.’s analysis of barriers to the use of eye protection (Xxxxxxxx et al. 2009). The bottom two levels in the HOC represent behavioral controls that they seek to change the way people work (for a summary of the limitations of these controls see Xxxxxxx, 2006). Each level of the HOC was given a rating ranging from one (personal protective equipment) to five (elimination). The risk controls implemented for hazards/risks presented by each feature of work were assigned a score on this five point scale. In the event that no risk controls were implemented, a value of zero was assigned. Independent variable Social network analysis (SNA) was used to map the social relations between participants involved in making design decisions about each feature of work. SNA is an analytical tool to study the exchange of resources between participants in a social network. Using social network analysis, patterns of social relations can be represented in the form of visual models (known as sociograms) and described in terms of quantifiable indicators of network attributes. In a sociogram, participants are represented as nodes. To varying extents, these nodes are connected by links which represent the relationships between participants in the network. SNA has been recommended as a useful method for understanding and quantifying the roles and relationships between construction project participants (Xxxxx, 2004; Xxxxxxxxx et al. 2008). The technique has been used to analyse analyze knowledge flows between professional contributors to project decision-making (see, for example, Xxxx et al. 2012; Xxxxx et al. 2013). Network characteristics have also been used to explain failures in team-based design tasks (Xxxxxxxxx et al. 2008) and identify barriers to collaboration that arise as a result of functional or geographic segregation in construction organizations (Xxxxxxxxx et al. 2010). More recently, Xxxxxxxxxx et al. (2013) used SNA to investigate the relationship between safety communication patterns and OSH performance in construction work crews. In order to gauge the construction contractor’s prominence in a project social network, the contractor’s degree centrality was calculated. Degree centrality refers to the extent to which one participant is connected to other participants in a network. Thus, degree centrality is the ratio of the number of relationships the actor has relative to the maximum possible number of relationships that the network participant could have. If a network participant possesses high degree centrality then they are highly involved in communication within the network relative to others. Xxxxx (2005) argues that degree centrality is a useful indicator of power and influence within a network. Degree centrality can be measured by combining the number of lines of communication into and out of a node in the network (see, for example, Alsamadani et al., 2013). This presents an aggregate value representing the participant’s communication activity. However, the independent variable used in this research was calculated using only the construction contractors’ outgoing communication. This was a deliberate choice because the research aim was to investigate whether OSH risk control is of a higher quality when project decisions are made with due consideration of construction process knowledge. Thus, the flow of communication from the construction contractor to other network members was deemed to be of greater relevance that the volume of information they received. From: Xxxxxxxxx, X., Xxxxxxx, X., Xxxxxxx, N., Xxxxxxxx, P., Xxxxxxx, B., Xxxxx, X., XxXxx, X. & Xxxxxxxx, X. (2014). ‘Construction Hazard Prevention: The Need to Integrate Process Knowledge into Product Design’. Paper presented at the CIB W099 International Conference: Achieving Sustainable Construction Health and Safety, 2-3 June 2014 Lund, Sweden.

Case Study Analysis. Dependent variable Data was collected about OSH hazards and the risk control solutions implemented within the case examples. This data was elicited during the interviews and supplemented with site-based observations and examination of project documentation (e.g. plans and drawings). For each feature of work, a score was generated reflecting the quality of implemented risk control solutions. This score was based on the hierarchy of control (HOC). The Hierarchy of Control classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control The hierarchy of control (HOC) is a well-established framework in OSH (see, for example, Xxxxxxx, 2006). The HOC classifies ways of dealing with OSH hazards/risks according to the level of effectiveness of the control. At the top of the HOC is the elimination of a hazard/risk altogether. This is the most effective form of control because the physical removal of the hazard/risk from the work environment means that workers are not exposed to it. The second level of control is substitution. This involves replacing something that produces a hazard with something less hazardous. At the third level in the HOC are engineering controls, which isolate people from hazards. The top three levels of control (i.e, elimination, substitution and engineering) are technological because they act on changing the physical work environment. Beneath the technological controls, level four controls are administrative in nature, such as developing safe work procedures or implementing a job rotation scheme to limit exposure. At the bottom of the hierarchy at level five is personal protective equipment (PPE) – the lowest form of control. Although, much emphasized and visible on a worksite, at best, PPE should be seen as a “last resort,” see, for example Xxxxxxxx et al.’s analysis of barriers to the use of eye protection (Xxxxxxxx et al. 2009). The bottom two levels in the HOC represent behavioral controls that they seek to change the way people work (for a summary of the limitations of these controls see Xxxxxxx, 2006). Each level of the HOC was given a rating ranging from one (personal protective equipment) to five (elimination). The risk controls implemented for hazards/risks presented by each feature of work were assigned a score on this five point scale. In the event that no risk controls were implemented, a value of zero was assigned. Independent variable Social network analysis (SNA) was used to map the social relations between participants involved in making design decisions about each feature of work. SNA is an analytical tool to study the exchange of resources between participants in a social network. Using social network analysis, patterns of social relations can be represented in the form of visual models (known as sociograms) and described in terms of quantifiable indicators of network attributes. In a sociogram, participants are represented as nodes. To varying extents, these nodes are connected by links which represent the relationships between participants in the network. SNA has been recommended as a useful method for understanding and quantifying the roles and relationships between construction project participants (Xxxxx, 2004; Xxxxxxxxx et al. 2008). The technique has been used to analyse knowledge flows between professional contributors to project decision-making (see, for example, Xxxx et al. 2012; Xxxxx et al. 2013). Network characteristics have also been used to explain failures in team-based design tasks (Xxxxxxxxx et al. 2008) and identify barriers to collaboration that arise as a result of functional or geographic segregation in construction organizations (Xxxxxxxxx et al. 2010). More recently, Xxxxxxxxxx et al. (2013) used SNA to investigate the relationship between safety communication patterns and OSH performance in construction work crews. In order to gauge the construction contractor’s prominence in a project social network, the contractor’s degree centrality was calculated. Degree centrality refers to the extent to which one participant is connected to other participants in a network. Thus, degree centrality is the ratio of the number of relationships the actor has relative to the maximum possible number of relationships that the network participant could have. If a network participant possesses high degree centrality then they are highly involved in communication within the network relative to others. Xxxxx (2005) argues that degree centrality is a useful indicator of power and influence within a network. Degree centrality can be measured by combining the number of lines of communication into and out of a node in the network (see, for example, Alsamadani et al., 2013). This presents an aggregate value representing the participant’s communication activity. However, the independent variable used in this research was calculated using only the construction contractors’ outgoing communication. This was a deliberate choice because the research aim was to investigate whether OSH risk control is of a higher quality when project decisions are made with due consideration of construction process knowledge. Thus, the flow of communication from the construction contractor to other network members was deemed to be of greater relevance that the volume of information they received. From: Xxxxxxxxx, X.R., Xxxxxxx, X., Xxxxxxx, N., Xxxxxxxx, P., Xxxxxxx, B., Xxxxx, X., XxXxx, X. & Xxxxxxxx, X. (2014). ‘Construction Hazard Prevention: The Need to Integrate Process Knowledge into Product Design’. Paper presented at the CIB W099 International Conference: Achieving Sustainable Construction Health and Safety, 2-3 June 2014 Lund, Sweden.