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Buildings are major contributors to greenhouse gases (GHG) along the various stages of the building life cycle. A range of tools have been utilised for estimating building energy use and environmental impacts; these are time-consuming and require massive data that are not necessarily available during early design stages. Therefore, this study aimed to develop an Environmental Impacts Cost Assessment Model (EICAM) that quantifies both energy and environmental costs for residential buildings.

An Artificial Neural Network (ANN) was employed to develop the EICAM. The model consists of six input parameters, including wall type, roof type, glazing type, window to wall ratio (WWR), shading device and building orientation. In addition, the model calculates four measures: annual energy cost, operational carbon over 20 years, envelope embodied carbon and total carbon per square metre. The ANN architecture is 6:13:4:4, where the conjugate gradient algorithm was applied to train the model and minimise the mean squared error (MSE). Furthermore, regression analysis for the ANN prediction for each output was performed.

The MSE was minimised to 0.016 while training the model. Also, the correlation between each ANN output and the actual output was very strong, with an R² value for each output of almost 0.998. Moreover, validation was conducted for each output, with the error percentages calculated at 0.26%, 0.25%, 0.03% and 0.27% for the annual energy cost, operational carbon, envelope materials embodied carbon and total carbon per square metre, respectively. Accordingly, the EICAM contributes to enhancing design decision-making concerning energy consumption and carbon emissions in the early design stages.

This study provides theoretical implications to the domain of building environmental impact assessment through illustrating a systematic approach for developing an energy-based prediction model that generates four environmental-oriented outputs, namely energy cost, operational energy carbon, envelope embodied carbon, and total carbon. The model developed has practical implications for the architectural/engineering (A/E) industries by providing a useful tool to easily predict environmental impact costs during the early design phase. This would enable designers in Saudi Arabia to make effective design decisions that would increase sustainability in the building life cycle.

By providing a holistic predictive model entitled EICAM, this study endeavours to bridge the gap between energy costs and environmental impacts in a predictive model for Saudi residential units. The novelty of this model is that it is an alternative tool that quantifies both energy cost, as well as building’s environmental impact, in one model by using a machine learning approach. Besides, EICAM predicts its outcomes more quickly than conventional tools such as DesignBuilder and is reliable for predicting accurate environmental impact costs during early design stages.

The prime aim of this paper is the identification and prioritization of performance indicators, which motivate the development of an Internet of Things (IoT)-based traceability system for the agriculture supply chain (ASC). Also, this research aims for checking the robustness of obtained results.

Ten performance indicators have been identified based on the five “criteria in the IoT-based traceable system”. Further, based on five criteria, performance indicators were ranked by using grey-based “Additive Ratio Assessment”.

Sustainable practices obtained first rank, and certification of agri-products obtained worst ranking. Further, based on sensitivity analysis, tracking of agri-products and stakeholders' behavior have found high sensitivity. Also, information sharing and global distribution networks have found the least sensitive performance indicators.

This research has some limitations of taking only a few criteria and alternatives. This study may also contribute as a practical insight to the practitioners and managers in decision-making in the adoption of an IoT-based traceable system within the ASC.

This research may motivate the implementation of an IoT-based efficient traceability mechanism that improved the sustainability and consumer's trust in the ASC during different types of hazardous activities and other outbreaks (COVID-19). Also, this research has provided a theoretical insight based on the dynamic capability theory (DCT).

We propose an oversampling technique to increase the true positive rate (sensitivity) in classifying imbalanced datasets (i.e., those with a value for the target variable that occurs with a small frequency) and hence boost the overall performance measurements such as balanced accuracy, G-mean and area under the receiver operating characteristic (ROC) curve, AUC. This oversampling method is based on the idea of applying the Synthetic Minority Oversampling Technique (SMOTE) on only a selective portion of the dataset instead of the entire dataset. We demonstrate the effectiveness of our oversampling method with four real and simulated datasets generated from three models.

Purpose: Entrepreneurial teams are one of the most crystallized forms of collaboration in the generically collective dynamics underpinning social entrepreneurship. Despite their quantitative prevalence, social entrepreneurial teams (SETs) remain quite absent from the scholarly literature. This chapter aims to develop a research agenda addressing this gap. Methodology/Approach: This chapter first reviews the scarce literature dealing with this subject and develops an operationalizable definition of SETs. Next, it confronts current knowledge on entrepreneurial teams with the specific context of social entrepreneurship to introduce and discuss main topics of investigation on SETs. Findings: Six topics are suggested to have a high potential for developing knowledge on SETs: formation, size and extended team, gender, decision-making and leadership, identity, and turnover. Research Implications: This chapter frames these research avenues within a developmental stages perspective with the aim to contribute to help form and maintain effective SETs. Originality/Value of Chapter: This research has implications for scholars as it defines SETs as a distinct object for research, which allows extending knowledge on collaborative dynamics in social entrepreneurship, but also on entrepreneurial teams in general. The suggested research agenda and its orientation toward the development of effective SETs should be a springboard for future research on this subject.

The chapter outlines the main forms of diasporas' contributions to the economic development and growth along with the determinants of their scale and scope. It then focuses on the diasporas' economic potential through participation in labour markets as an international staffing option at the level of individual organizations. Both the opportunities and threats of using diaspora members in international staffing are discussed. Finally, possible directions for future research are identified.

That photography was more than a mere technological breakthrough was clear to its inventors but not to their contemporaries or generations after. The fast visual appropriation of “reality,” the sudden transformation of this reality into an image which mirrored our world, gave us a new lease on immortality. From its inception, photography became an act of assertion and vainglory and biographers could study the psychology of a face as well as the depth of the soul. Walt Whitman once wrote: “I've been photographed, photographed, and photographed until the cameras themselves are tired of me.” (As quoted by Justin Kaplan. Walt Whitman. A Life. Simon & Schuster, 1980.) From Whitman's ego trips to the forced smiles in that brief but powerful scene in the film, Ordinary People, when family soul‐searching is captured by the click of a camera, the world around us is preserved and mythologized. Photography is witness to history and art, and shapes our lives as well. In a recent interview, Mikhail Baryshnikov stated that as a dancer he had been influenced not only by other choreographers but by “movies, musicals,(and) photo exhibitions.” (The New York Times, June 28, 1981, p. 6). Thus, photography becomes archival material, for it speaks of the human adventure in all its diversity.

From the perspective of business history, this chapter presents an overview of the development of the tourism sector in South America, placing special emphasis on the Peruvian case. The chapter explores various topics related to the tourism chain, such as hotel networks, the role of the state, tour operators, micro- and small enterprises, linkages between tourism and sustainability, the formation of clusters in the sector, and interactions between different entrepreneurs in the chain. Special emphasis is placed on the Peruvian case, especially when it comes to discussing the role of micro- and small enterprises in the sector.