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Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

Despite the contributions of both the oil and gas and construction industries to the gross domestic product (GDP) of the country, both industries are still marred by incessant accidents. Therefore, the aim of this study is to compare the health and safety practises of the construction and oil and gas industries in Nigeria in order to suggest the best approach to health and safety practices.

A survey questionnaire was developed and administered to professionals working in the construction and oil and gas industries. Data were analysed using the relative importance index (RII). An independent sample t-test was also conducted to determine whether there was a significant difference in the construction and oil and gas industries.

The study revealed that the rate at which health and safety are practised in the oil and gas industry is comparatively high compared to how they are practised in the construction industry. Proper site layout and planning, provision of a safe working environment, proper health and safety risk assessment were more predominantly practised in the oil and gas industry, while proper site layout and planning, disallowing unauthorised entry into site and the provision of a safe working environment were predominantly practised in the construction industry.

This study is the first to compare the health and safety practises of the construction and oil and gas industries in Nigeria. This study was significant because it would provide insight into construction and oil and gas managers, as well as other decision-makers in both industries, on how to improve health and safety practices.

Safety and security (S&S) are critical concerns in South Africa, especially in Cape Town, one of the country’s most crime-ridden cities. The University of Cape Town (UCT), situated on a large, open campus, has experienced increased malefaction. Facilities management (FM) services at universities bear the primary responsibility for providing S&S to their communities. To comprehensively understand and address the community’s demands regarding S&S, the current study was conducted to investigate the challenges specific to open universities. This study aims to determine whether implementing community-based FM (CbFM) principles and using technological innovations could offer a more effective and sustainable solution.

The study adopted interpretivist overarching case study methodology, which is ontologically based. A mixed-method approach was used to incorporate the strengths and limitations of the weaknesses of both methods. The data collection took the form of an online survey of the university community and semi-structured interviews with university executive management to obtain data from the single case study of UCT. Descriptive statistics were used to analyze the quantitative data, and thematic analysis was used to identify emergent themes from the qualitative data.

The study presents an overall view of the provision of S&S at UCT, the unique challenges faced by management and the main S&S issues affecting the community. Moreover, the study reveals that UCT has implemented community participation processes in the past with limited success. This is because the strategies implemented constitute a narrow perspective of community participation. Therefore, a much smarter and more inclusive perspective using technological innovation is required for successful community participation to occur and to be successfully used in providing S&S toward achieving future-proofing facilities.

This research has demonstrated the influence of CbFM and innovative technologies on the S&S of the open campus. Hence, future-proof facilities can be achieved when FM actively engages university communities in managing campuses through technological innovation.

There is a robust study on crime prevention through environmental design (CPTED) in student housing nowadays, but has a limited utilization of weight-of-evidence (W-o-E) approach. This study aims to assess the extent of CPTED in student housing facilities of universities in Ghana.

Using the on-campus student housing facilities of both private and public universities, the study adopted W-o-E approach that integrates two postoccupancy evaluations from end-users and student housing managers. In addition, observation by professionals as the lines of evidence (LoE) was also adopted. Weighted median was used to normalise the LoE into a W-o-E as the CPTED value in the student housing facilities.

The study uncovered low CPTED in the student housing facilities. Maintenance was identified as the leading CPTED principle present in the student housing facilities.

The study has given the extent of CPTED in students’ housing, an important insight for university students’ housing management. This can serve as a policy alert for the university students’ housing management to adopt building designs that enhance CPTED and the safety of the youth.

This study is different from other CPTED and students’ housing studies commonly situated in the Euro-America context. The study exceptionally applied the use of W-o-E in students’ housing in assessing the extent of CPTED in student housing within the context of sub-Saharan African universities.

The aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

The case describes the structure of Infrastructure Investment Trusts (InvITs) created and launched in Indian markets in 2017. Besides introducing InvITs and their potential role in relaxing the financing constraint created by the lack of an active corporate debt market in India, the case can help in analysing why the market is discounting the IndiGrid unit price relative to its issue price. It also offers an opportunity to value IndiGrid's Patran acquisition.

The paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.

This paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.

Simulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.

(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.