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Building-integrated greenery (BIG) systems, which include green roofs and green facades, are well-established nature-based solutions (NBS) with proven scientific benefits. However, initial costs and economic apprehensions stemming from potential negative outcomes act as adoption barriers. Furthermore, the lack of standardized indicators and assessment methodologies for evaluating the city-level impacts of BIG systems presents challenges for investors and policy makers. This paper addresses these issues by presenting a comprehensive set of indicators derived from widely accepted frameworks, such as the Common International Classification of Ecosystem Services (CICES) and the NBS impact evaluation handbook. These indicators contribute to the creation of a ‘sustainability factor’, which facilitates cost–benefit analyses for BIG projects using locally sourced data. The practical application of this factor to a 3500 m2 green roof in Lleida, Catalonia (Spain) demonstrates that allocating space for urban horticultural production (i.e., food production), CO2 capture, and creating new recreational areas produces benefits that outweigh the costs by a factor value of nine during the operational phase of the green roof. This cost–benefit analysis provides critical insights for investment decisions and public policies, especially considering the significant benefits at the city level associated with the implementation of BIG systems.

Building-integrated greenery (BIG) systems, which include green roofs and green facades, are well-established nature-based solutions (NBS) with proven scientific benefits. However, initial costs and economic apprehensions stemming from potential negative outcomes act as adoption barriers. Furthermore, the lack of standardized indicators and assessment methodologies for evaluating the city-level impacts of BIG systems presents challenges for investors and policy makers. This paper addresses these issues by presenting a comprehensive set of indicators derived from widely accepted frameworks, such as the Common International Classification of Ecosystem Services (CICES) and the NBS impact evaluation handbook. These indicators contribute to the creation of a ‘sustainability factor’, which facilitates cost–benefit analyses for BIG projects using locally sourced data. The practical application of this factor to a 3500 m2 green roof in Lleida, Catalonia (Spain) demonstrates that allocating space for urban horticultural production (i.e., food production), CO2 capture, and creating new recreational areas produces benefits that outweigh the costs by a factor value of nine during the operational phase of the green roof. This cost–benefit analysis provides critical insights for investment decisions and public policies, especially considering the significant benefits at the city level associated with the implementation of BIG systems.

The lodging industry increasingly relies on digital technology and innovations in various operations in order to develop a competitive strategy and improve their operational activities during the pandemic. Nowadays, digital transformation is a key element for business sustainability. This paper presents an industry case study involving four hotels or lodging companies operating in Chile which have successfully incorporated technology and new communication channels with their clients, carrying out a digital transformation that is key to the competitiveness and survival of their businesses. The results show that the impact of digitalization on sales and visibility of companies in the sector is huge; second, the effects of digital innovation on the management of key processes, both in the back office and in the front office, is very important; third, the incorporation of technology as a standard factor in order to be competitive in the industry is a key element; finally, the problems or obstacles that lodging companies must face in the process of implementing new information technologies. Without digital innovation, this sector would not have been able to survive in times of pandemic.

The lodging industry increasingly relies on digital technology and innovations in various operations in order to develop a competitive strategy and improve their operational activities during the pandemic. Nowadays, digital transformation is a key element for business sustainability. This paper presents an industry case study involving four hotels or lodging companies operating in Chile which have successfully incorporated technology and new communication channels with their clients, carrying out a digital transformation that is key to the competitiveness and survival of their businesses. The results show that the impact of digitalization on sales and visibility of companies in the sector is huge; second, the effects of digital innovation on the management of key processes, both in the back office and in the front office, is very important; third, the incorporation of technology as a standard factor in order to be competitive in the industry is a key element; finally, the problems or obstacles that lodging companies must face in the process of implementing new information technologies. Without digital innovation, this sector would not have been able to survive in times of pandemic.

Maintenance is one of the main drivers for ensuring the sustainability of manufacturing in capital-intensive production systems. However, in many cases, as a result of budgetary constraints, it is necessary to select which machines will be subject to maintenance actions on the basis of a list of priorities. Traditionally, such prioritization decisions are made using techniques which, in general, do not consider the systemic impact of maintenance actions. This paper is focused at the definition of a novel graphical technique for physical assets prioritization. This technique is aimed at establishing maintenance priorities considering the impact on the overall throughput of the production system. Due to the fact that the proposed technique is based on the well-known Overall Equipment Effectiveness (OEE) index, its use is not only limited to measuring the effects of maintenance decisions and actions (availability), but also to operational implications (productivity and utilization). The results could be displayed graphically, which makes it particularly useful and manageable for different types of users. The methodology is illustrated though an example based on a comminution plant from the copper mine industry. It is evident how the proposed technique facilitates business-oriented and economic sustainability focused decisions.

Maintenance is one of the main drivers for ensuring the sustainability of manufacturing in capital-intensive production systems. However, in many cases, as a result of budgetary constraints, it is necessary to select which machines will be subject to maintenance actions on the basis of a list of priorities. Traditionally, such prioritization decisions are made using techniques which, in general, do not consider the systemic impact of maintenance actions. This paper is focused at the definition of a novel graphical technique for physical assets prioritization. This technique is aimed at establishing maintenance priorities considering the impact on the overall throughput of the production system. Due to the fact that the proposed technique is based on the well-known Overall Equipment Effectiveness (OEE) index, its use is not only limited to measuring the effects of maintenance decisions and actions (availability), but also to operational implications (productivity and utilization). The results could be displayed graphically, which makes it particularly useful and manageable for different types of users. The methodology is illustrated though an example based on a comminution plant from the copper mine industry. It is evident how the proposed technique facilitates business-oriented and economic sustainability focused decisions.

The objective is to study the distribution of passengers inside urban trains for different levels of crowding. The study is carried out through the observation of videos made by laboratory experiments in which a mock-up of a carriage represented the boarding and alighting process. The Fruin’s Level of Service (LOS) was adopted, but with a different approach, in which the train is divided into five zones (central hall, central aisle, side aisle, central seats and side seats). The experiments are based on the behavior of passengers in the London Underground; however, this study could be expanded to any conventional rail or LRT system. For the laboratory experiments, it is proposed to build a metro carriage and a corresponding platform section, and the scenarios will include different levels of crowding of passengers boarding and alighting to produce a variation in the density on the platform. According to the crowding level, the results allow obtaining the distribution and movements generated by passengers in the five zones for different instants of time during the process of boarding and alighting. It is observed that passengers are distributed according to safety and efficiency conditions. For example, passengers tried to avoid contact with each other unless it is inevitable. In relation to comfort, the seats of the carriage are always used even if there is a low level of crowding. If the crowding level increases, the boarding and alighting time go up. In addition, passengers will spend one or two seconds more if the “let’s get off before getting on the carriage” behavior is breached. This kind of experiment can be used in further research as a way to test “what-if” scenarios using this new method of discretization of the space inside the train, which cannot be tested in existing stations due to restrictions such as the weather, variability of the train frequency, current design of the trains, among others. New experiments are necessary for future research to include other types of passengers such as people with disabilities or reduced mobility.