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The paper investigates how visibility, information technology and innovation management impact sustainability performance. It proposes a framework explaining the role of visibility in driving firms' sustainable performance and the relevance of innovation management and information technologies in enhancing organisational visibility. This study intends to add to the discussion within the management literature about the potential of innovation management to drive sustainability. It seeks to provide insight into the practices that small and medium-sized enterprises (SMEs) can adopt to improve their sustainable performance.

Using empirical methods, the study investigates SMEs in central Mexico. The demographic information in the dataset includes 15 years as an average length of service from firms. Of the surveyed firms, 70% were from the manufacturing sector and 30% were from the service sector, as these are the most representative sectors of the productive region. A variance-based structural equation model approach was used to test the hypotheses, processed with the partial least squares (PLS) regression method.

The research results show that visibility significantly impacts sustainability performance. Innovation management has a higher influence on visibility than information technologies, emphasising the need to improve the quality of information in firms, not just the tools. The findings support managers in comprehending the crucial importance of visibility in aiding firms to achieve higher sustainability performance.

The study only examined a sample of Mexican SMEs; therefore, the findings' generalizability must be considered within this context. Secondly, the survey only focused on services and manufacturing firms and a more detailed analysis of the sector could provide further clarity on the relationships between variables. As a result, future research should consider these limitations and explore additional contexts to improve the overall understanding of the topic. Moreover, the scale used to measure the variables was adapted from other researchers with similar context research and reflective variables.

The results provide helpful information for SME managers about the importance of focusing on innovation management processes and employing information technologies as crucial managerial strategies. This will aid in increasing visibility and supporting the development of sustainability performance in firms.

The world red-code, among others, with climate change and social gaps, has generated the need to contribute to sustainable development, and it has mobilised people on all levels all over the world for the simple purpose of preserving life. Therefore, society, as a crucial group that affects and is affected by this red-code situation, should act in favour of visibility, the use of high-quality information (e.g. transparent, accessible and relevant) and information technologies to promote sustainable practices. This could mean that society should be prepared to incorporate new capabilities and spaces to interchange knowledge as a participatory community that can contribute to better sustainable dynamics that could expand its participation in public decisions. Also, the government should encourage digital democracy (e.g. develop social participation platforms), opening and harmonising rules and mechanisms combining high-quality information with IT to provide flexible and adequate services that support sustainable development, such as efforts towards constructing sustainable and smart cities.

This study explores how innovation management can drive firms' sustainability performance, which is crucial for improving competitiveness. The question of how to enhance sustainability performance through managerial drivers is a critical one. This study empirically investigates the nexus of visibility and sustainability performance, innovation management and information technology with visibility.

Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process.

PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles.

PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one.

The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding.

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.

Exposure to indoor air pollutants poses a significant health risk, contributing to various ailments such as respiratory and cardiovascular diseases. These unhealthy consequences are specifically alarming for athletes during exercise due to their higher respiratory rate. Therefore, studying, predicting and curtailing exposure to indoor air contaminants during athletic activities is essential for fitness facilities. The objective of this study is to develop a neural network model designed for predicting optimal (in terms of health) occupancy intervals using monitored indoor air quality (IAQ) data.

This research study presents an innovative approach employing a long short-term memory (LSTM) recurrent neural network (RNN) to determine optimal occupancy intervals for ensuring the safety and well-being of occupants. The dataset was collected over a 3-month monitoring campaign, encompassing 15 meteorological and indoor environmental parameters monitored. All the parameters were monitored in 5-min intervals, resulting in a total of 77,520 data points. The dataset collection parameters included the building’s ventilation methods as well as the level of occupancy. Initial preprocessing involved computing the correlation matrix and identifying highly correlated variables to serve as inputs for the LSTM network model.

The findings underscore the efficacy of the proposed artificial intelligence model in forecasting indoor conditions, yielding highly specific predicted time slots. Using the training dataset and established threshold values, the model effectively identifies benign periods for occupancy. Validation of the predicted time slots is conducted utilizing features chosen from the correlation matrix and their corresponding standard ranges. Essentially, this process determines the ratio of recommended to non-recommended timing intervals.

Humans do not have the capacity to process this data and make such a relevant decision, though the complexity of the parameters of IAQ imposes significant barriers to human decision-making, artificial intelligence and machine learning systems, which are different. Present research utilizing multilayer perceptron (MLP) and LSTM algorithms for evaluating indoor air pollution levels lacks the capability to predict specific time slots. This study aims to fill this gap in evaluation methodologies. Therefore, the utilized LSTM-RNN model can provide a day-ahead prediction of indoor air pollutants, making its competency far beyond the human being’s and regular sensors' capacities.

The purpose of this study is to determine the characteristics of the studies in terms of country, participant profile and methodology, as well as to determine what the Internet of Things (IoT) is currently contributing to higher education.

The study was developed following the methodology supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the PICOS strategy, retrieving scientific literature from Web of Science, Scopus, ERIC and Google Scholar. Of the 237 studies that the search yielded, 11 were included.

The results showed that among the opportunities offered by IoT is that it not only brings the introduction of information and communication technology into the classroom, but also enhances student interest, thus, improving the quality of teaching in higher education. On the other hand, one of the challenges it faces is the attitude of teachers towards its adoption, as well as the level of digital competence of teachers.

This study presents how higher education institutions are including the IoT in their educational activities. The IoT refers to a network of digital interconnectivity between devices, people and the internet itself that enables the exchange of data between them, allowing key information about the use and performance of devices and objects to be captured to detect patterns, make recommendations, improve efficiency and create better user experiences.