# Advancing BIM and Sustainability with Coopetition: Evidence from the Portuguese Stone Industry
## 8 Measuring the Impact of Coopetition vs. No Coopetition  
This study evaluates coopetition against scenarios where such interactions are absent (no coopetition). The objective is to understand how coopetition influences the KPIs mentioned above in a manufacturing context. The independent variables considered include Parts Delivered, Parts Delivered On Time, Parts Shipped, Labour Hours Involved, Energy Consumed, and Parts Produced. These variables reflect the companies' operational efficiency, productivity, and sustainability.  
To distinguish between cooperative and non-coopetition scenarios, the study employs a comparative analysis of company outputs during periods of active cooperation and periods when companies operated independently (no cooperation).  
This approach evaluated the transition from current practices (CB.P) to a new concept of practices, referred to as coopetition network practices (CN.P), where companies, facilitated by the Cockpit4.0+, share manufacturing resources and raw material stocks to capture market opportunities from BIM users.  
The CN.P phase involved structured collaborations among companies, sharing resources, knowledge, and logistics while maintaining competitive aspects. Current practices (CB.P) refer to the no-coopetition phase, a period when companies operate without such collaborative interactions, relying solely on their internal capabilities and strategies.  
The independent variables were measured as follows:  
* Parts Delivered: The total number of parts delivered to customers during the observation period.
* Parts Delivered On Time: The percentage of parts delivered within the agreed-upon time frame, reflecting the companies' ability to meet deadlines.
* Parts Shipped: The total number of parts shipped out, indicating the companies' logistical and production capabilities.
* Labour Hours Involved (h): The total labour hours expended in production provide insight into workforce efficiency and productivity.
* Energy Consumed (kWh): The total energy consumed during production, which is critical for assessing sustainability and energy efficiency.
* Parts Produced: The total number of parts manufactured during the period, reflecting overall production output.  
The study acknowledges that the outputs of the companies could be influenced by other factors, such as time lapses or learning effects. To isolate the impact of coopetition, these potential confounding factors were controlled by comparing performance metrics during similar time periods and by normalizing data to account for seasonal variations or other external influences. This approach helps ensure that the observed differences in performance metrics can be more confidently attributed to the presence or absence of co-opetition.  
Coopetition, as a strategic approach, can be considered a latent (hidden) variable that influences the observed outputs. This study operationalizes coopetition through structured interactions between companies, such as joint resource utilization, shared logistics, and coordinated production schedules. By comparing the independent variables under co-opetition and non-coopetition scenarios, the study aims to reveal the underlying effects of coopetition on operational performance.  
To strengthen the analysis, additional qualitative insights were gathered from company management and operational staff to understand the nature and extent of competition during the study period. This helped contextualize the quantitative findings and provided a clearer picture of how coopetition practices were implemented and their perceived impact on company performance.