Search

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI is on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is two-fold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research.

Purpose: Businesses produce corporate sustainability information in support of the decision-making of their stakeholders through sustainability reporting. However, the use of such information has been limited because of the broadness of sustainability indicators used in sustainability reports. This study aims to identify sector-specific sustainability indicators and priorities based on the material issues of the logistics sector. Design/methodology/approach: The authors conducted an exploratory study using 64 sustainability reports from the logistics sector. Qualitative content analysis was performed using Leximancer software to identify key themes and material concepts of sustainability reports. Findings: The results showed that the most important indicators of the logistics sector are economic performance and energy, yet sustainability reports appear to focus more on reporting social sustainability information. Of the several sustainability measures, environmental and social factors dominated the reporting (8 economic, 62 environmental and 58 social). This discrepancy can also imply inconsistencies in sustainability reporting. Practical implications: Identifying sector-specific indicators enables assessing the impact of sustainability issues on value creation and performance comparison among similar organizations. This is also beneficial in ensuring consistency of sustainability reporting, which is a prerequisite for policymaking in sustainable logistics. Originality/value: Prior studies emphasized that no sector-specific sustainability indicators were established in the literature and standardized indicators are needed to ensure the comparability of results. This study addresses this gap by identifying sector-specific sustainability indicators based on the material issues of the logistics sector.

Transforming toward a circular economy (CE) is a viable strategy for achieving sustainable logistics systems. However, it is still unclear how this transformation should be approached because there is limited knowledge in this context. This study aims to explore how the logistics sector incorporates sustainability practices toward CE. To achieve this aim, we addressed the research questions of (RQ1) what sustainability practices are used by the logistics sector and (RQ2) how these practices contribute to transforming the logistics sector into CE. We used a qualitative approach to address these questions by interviewing 14 logistics service providers. Interview transcripts were analyzed by using coding, categorizing, and finding relationships among the concepts identified from the literature following the Gioia method. We identified 47 sustainable logistics practices under nine categories from three key themes: environmental preservation, firm's dynamic capabilities, and social well-being. We used the natural resource-based view, dynamic capabilities, and social well-being theories to identify the key themes. These theories contributed to the existing knowledge on CE strategies from the aspects of environmental, economic, and social value in transforming the logistics sector into CE. We built three propositions based on the findings and the propositions highlight that economic value creation is the core benefit followed by environmental and social value creation in the CE transformation. The identified three themes will provide a holistic approach for implementing CE within the logistics sector.

Managing supply chain performance is essential for value generation to stakeholders. Nonetheless, this process has become overly complicated due to environmental concerns that lead to policy changes, customer preferences, and business activities. Reverse logistics is an environmentally friendly practice that can be critical in improving the environmental performance of construction operations. This paper examines the perceived role of reverse logistics practices on supply chain performance criteria—for example, cost, quality, time, flexibility, and environment. Semistructured in-depth interviews were conducted with 15 senior industry experts from South East Queensland, Australia. Interview transcripts were analyzed by coding, categorizing, and identifying the interconnected relationships among concepts. In general, the experts perceive that reverse logistics practices significantly reduce the sourcing cost of materials compared with new materials. When used materials meet industry specifications, they are expected to have a similar performance without affecting the construction time or the overall quality of the project while protecting the environment. Nevertheless, the flexibility is found to be somewhat difficult. It is likely that reverse logistics can be instrumental in construction should the industry uptake be substantial with an emphasis on used material quality and acceptance criteria. Hence, a quantitative analysis is encouraged for future research.

There are several methods available for modeling sustainable supply chain and logistics (SSCL) issues. Multi-objective optimization (MOO) has been a widely used method in SSCL modeling (SSCLM), nonetheless selecting a suitable optimization technique and solution method is still of interest as model performance is highly dependent on decision-making variables of the model development process. This study provides insights from the analysis of 95 scholarly articles to identify research gaps in the MOO for SSCLM and to assist decision-makers in selecting suitable MOO techniques and solution methods. The results of the analysis indicate that economic and environmental aspects of sustainability are the main context of SSCLM, where the social aspect is still limited. More SSCLMs for sourcing, distribution, and transportation phases of the supply chain are required. Additionally, more sophisticated techniques and solution methods, including hybrid metaheuristics approaches, are needed in SSCLM.

This chapter addresses the root causes of the lack of enthusiasm and technologies that other industries and other sectors are warmly embracing. It discusses information management that pertains to integrated project delivery (IPD) and the impact of Big Data in the built environment. The chapter provides an overview of the data-management practices in the construction industry, its relationship with IPD, and a succinct summary of opportunities in the future. It summarizes the need for a holistic approach to information technology management, discuss some potential applications in the built environment and introduce our data-management protocol which can seamlessly integrate across many applications to enable improved capability. Consider a practical application where travel speed and travel volume towards the airport could inform staff about the expected fluctuation in demand on check-in counters, facility usage and service requirements. The general ontology is used for data discovery, negotiation of delivery format, and connecting data with available tools and algorithms for manipulation.

Most of the construction materials still go to landfill after structures are demolished. This causes issues in human health, ecosystem preservation, and excessive resource consumption compared to RL options. Hence, recovering material value through reverse logistics (RL) is important to lessen the environmental and social burden. Embodying RL practices into strategic level decisions derives long-term and sustainable advantages. Although the most common RL option in construction seems to be recycling, it requires an additional energy and material intensive process. Therefore, recycling should be the last preference among other RL options. The hypothesis of this study is that alternative RL strategies provide more environmental benefits than recycling, the most common RL method, and traditional landfilling. The hypothesis was tested through assessment of the environmental impact of RL options in the construction sector. A life cycle assessment (LCA) with ReCipe2016 Midpoint and Endpoint assessment method was conducted for a bridge construction supply chain. Different end-of-life scenarios such as reuse, remanufacture, recycle, and landfill scenarios were assessed using SimaPro software. This paper addresses a key knowledge gap on the environmental impact of reverse logistics strategies from a construction supply chain perspective. The research results reveal that “reuse” strategy has the least environmental impact, remanufacturing has a lesser impact on the environment than other options, recycling has the second highest environmental impact, with landfill assessed as the least environmentally friendly end-of-life option. Consequently, this paper emphasizes the importance of informed strategic supply chain decisions for reverse logistics to obtain the best outcome from environmentally friendly practices. Since there is no relevant previous research conducted to examine the environmental impact of different reverse logistics options from a construction supply chain

After the onset of the recent COVID-19 pandemic, a number of studies reported on possible changes in electricity consumption trends. The overall theme of these reports was that “electricity use has decreased during the pandemic, but the power grid is still reliable”—mostly due to reduced economic activity. In this paper, we analyze electricity data until the end of May 2020, examining both electricity demand and variables that can indicate stress on the power grid. We limit this study to three states in the U.S. California, Florida and New York. The results indicate that the effect of the pandemic on electricity demand is not a simple reduction, and there are noticeable differences among regions analyzed. The variables that can indicate stress on the grid (e.g., daily peak and trough of the hourly demand, demand ramp rate, demand forecast error, and net electricity interchange) also conveyed mixed messages: some indicate an increase in stress, some indicate a decrease, and some do not indicate any clear difference. A positive message is that some of the changes that were observed around the time stay-at-home orders were issued appeared to revert back by May 2020. A key challenge in ascribing any observed change to the pandemic is correcting for weather as it can be challenging to accurately define it for large geographic regions. We provide a weather-correction method, apply it to a small city-wide area in North Central Florida, and discuss the implications of the estimated changes in demand. The results indicate that a 10% (95% CI [2%, 18%]) increase in electricity demand is likely to have occurred due to COVID-19 for the city analyzed.

Improving the quality of infrastructure is crucial for sustainable development. Providing infrastructure faces many challenges – both financially and in terms of how projects are delivered. This is particularly apparent for developing countries. This research aims to (a) determine the key factors influencing the successful delivery of infrastructure projects, (b) provide an example of these factors as manifested on an important Ecuadorian flood control and irrigation infrastructure project, and (c) identify key learnings for future projects in similar contexts. Many of the key failure factors identified in the literature were evident on the example project, validating the literature findings and indicating that the learnings may be relevant to the context of developing countries more widely. These factors included insufficient planning, unrealistic estimates, poor stakeholder communication, bureaucracy, insufficient ground investigation and an inadequate project delivery system. Addressing these issues is an important step towards improving infrastructure delivery in developing countries.

Innovation ambidexterity is the simultaneous persuasion of incremental and radical innovation by an organisation to achieve short- and long-term competence in business. Construction Project-Based Small and Medium size Enterprises (PB-SMEs) are facing industry-driven push to uptake incremental and radical innovation emanates from technological advancement and escalating regulatory targets for energy efficiency. This poses construction PB-SMEs towards rapid adoption of not just incremental innovation for competent project delivery at present, also radical innovation for future competiveness such as competence to adopt smart construction systems. Research supports that the adoption of innovation is facilitated by effective knowledge sharing. As the one-off nature of project operation acts as a barrier to seamless transfer of knowledge across projects, so effectively sharing of innovation knowledge is challenging. Moreover, knowledge sharing is a social phenomenon, and willingness to share knowledge is impacted by the extent of sharer’s social embeddedness. The theory of social capital emphasises that actors’ embedment in network relationship can offer additional beneficial resources from network engagement. Although project operation is discontinuous in nature, it provides construction PB-SMEs the scopes to involve in various network engagements within the construction industry. These network engagements may lead to gradual establishment of social capital so as to offer additional resources to overcome disadvantages of project discontinuity. However, the impacts of social capital on innovation knowledge sharing to facilitate rapid adoption of innovation by construction PB-SMEs are yet to explore in research. This paper provides a conceptual framework to explore the impacts of social capital dimensions of construction PB-SMEs on innovation knowledge sharing in order to facilitate rapid adoption of innovation to help achieve concurrent incremental and radical innovation.

Construction industry activities, from material extraction to the end of the structure life, affect the environment negatively. For a sustainable construction process, economically, environmentally, and socially friendly practices are essential, and reverse logistics is one solution that can provide such an approach. In reverse logistics, obsolete products are reused in a new production, while reducing negative effects to the environment. In this study, we assess the current state of research on reverse logistics practices in the construction industry. The study presents a comparative data mining analysis, followed by a content analysis. The results show that the construction industry literature ignores the impact of reverse logistics practices on upstream construction activities. We argue that industry practitioners must take reverse logistics decisions in the early phases of the construction process by considering both upstream and end-of-life construction activities, and we recommend a reverse logistics decision framework for successful reverse logistics implementation. The findings of this research are significant for decision-makers in the industry. We urge that sustainable practices be employed in the industry. Furthermore, a quantitative analysis is suggested to strengthen the arguments made in this article.

Urban Heat Islands (UHIs) are problematic in subtropical climates and their impact is worse in extreme weather conditions. Green infrastructure such as green roofs and green walls can offer potential benefits. This includes; reducing heat impact on buildings, reducing use of air conditioning (thereby providing energy savings), reducing the effects of UHI (i.e. glare from surrounding structures) and improving employee health and well-being, reducing mental fatigue and promoting work productivity. Temporary accommodation or temporary work buildings can potentially benefit from green infrastructure through cooling the building, thereby reducing the need for air conditioning. However, to date, there is no evidence to suggest whether this is a viable solution.

This article aims to identify the main risk factors that are threats to meet the objectives of tunnel construction projects by using the Chilean construction industry as a case study and proposes a methodology to evaluate risk factors in this type of project. Surveys were used to generate probability and severity indexes to rank 36 risk factors. Data were collected from 14 companies that are members of the International Tunneling and Underground Space Association. The results indicate that the main risk factors that hinder achieving the tunneling construction project objectives are (1) inaccurate cost estimation or lack of detail in budget preparation, (2) unexpected geological conditions, (3) inaccurate deadline estimation or insufficient break- down of the project schedule, (4) frequent malfunction of construction equipment, (5) excessive delays in approval processes by government entities, and (6) unexpected soil conditions and water table. Furthermore, a comprehensive literature review is provided to compare these results to international perspectives to confirm the existence of risks inherent to tunnel construction projects. This article concludes with revisiting the risk factors, which are common for the construction industry in general.

The Time/Cost Trade-off (TCT) problem has long been a popular optimization question for construction engineering and management researchers. The problem manifests itself as the opti- mization of total costs of construction projects that consist of indirect project costs and individual activity costs. The trade-off occurs as project duration and, as a result, indirect project costs de- crease with reduced individual activity duration. This reduction in individual activity duration is achieved by increasing resource allocation to individual activities, which increases their costs to completion. Historically, metaheuristic solutions have been applied to small scale problems due to computational complexities and requirements of larger networks. In this paper, we demonstrate that the metaheuristic approach is highly effective for solving large scale construction TCT problems. A custom Genetic Algorithm (GA) is developed and used to solve large benchmark networks of up to 630 variables with high levels of accuracy (<3% deviation) consistently using computational power of a personal computer in under ten minutes. The same method can also be used to solve larger net- works of up to 6,300 variables with reasonable accuracy (∼7% deviation) at the expense of longerprocessing times. A number of simple, yet effective, techniques that improve GA performance for TCT problems are demonstrated; the most effective of which is a novel problem encoding, based on weighted graphs, that enables the critical path problem to be partially solved for all candidate solutions a priori, thus significantly increasing fitness evaluation. Other improvements include parallel fitness evaluations, optimal algorithm parameters, and the addition of a stagnation criteria. We also present some guidelines of optimal algorithm parameter selection through a comprehensive parameter sweep and a computational demand profile analysis. Moreover, the methods proposed in this article are based on open source develo

The goal of this study is to explore the perceptions and behaviours of drivers who cruise for parking. We conducted surveys with drivers in Brisbane, Australia, to understand potential factors that influence driver’s cruising behaviour. This study reveals that the errors in drivers’ perception of the parking cost are one of the leading factors encouraging drivers to cruise for on-street parking. Drivers are not necessarily well informed about parking costs, even when they claim to be familiar with these costs. The survey also reveals that the more informed drivers are about the local traffic and parking conditions, the less likely they are to cruise for extended periods of time. This finding demonstrates the value of traffic and parking information to effectively mitigate cruising for parking. The interview results also demonstrate that the on-street parking premium (i.e., accessibility or convenience factor) could be much larger than our common assumptions, and a significant contributor to increased cruising time. Finally, this study introduces the sunk cruising cost and its potential impact on cruising time. Our hypothesis is that the effect of sunk cost may be manifest in a greater tendency to continue cruising because the cruising time spent is simply unrecoverable past expenditure. The survey data supports our hypothesis, and with findings on the drivers’ misperception about the parking cost and the familiarity factor, this result highlights the value of accurate and timely parking cost and availability information to drivers to tackle the cruising for parking issue.

Finishing highway projects within budget is critical for state highway agencies (SHAs) because budget overruns can result in severe damage to their reputation and credibility. Cost overruns in highway projects have plagued public agencies globally. Hence, this research aims to develop a parametric cost estimation model for SHAs to forecast the completed project cost prior to project execution to take necessary measures to prevent cost escalation. Ordinary least square (OLS) regression has been a commonly used parametric estimation method in the literature. However, OLS regression has certain limitations. It, for instance, requires strict statistical assumptions. This paper proposes an alternative approach—least absolute shrinkage and selection operator (LASSO)—that has proved in other fields of research to be significantly better than the OLS method in many respects, including automatic feature selection, the ability to handle highly correlated data, ease of interpretability, and numerical stability of the model predictions. Another contribution to the body of knowledge is that this study simultaneously explores project-related variables with some economic factors that have not been used in previous research, but economic conditions are widely considered to be influential on highway construction costs. The data were separated into two groups: one for training the model and the other for validation purposes. Using the same dataset, both LASSO and OLS were used to build models, and then their performance was evaluated based on the mean absolute error, mean absolute percentage error, and root mean square error. The results showed that the LASSO regression model outperformed the OLS regression model based on the criteria.

This study explores the perceptions and behaviours of drivers that pertain to cruising for parking and their impact on the time of cruising for parking. A survey was conducted with drivers in the Southbank district of city of Brisbane, Australia through face-to-face interviews. This district is Brisbane’s cultural and recreational precinct and one of most popular tourist attractions where severe congestion is frequently seen during the afternoon peak-hours because of visitors and commuting traffic. The survey reveals that potential errors in drivers’ perception of the parking cost are one of the major drivers of the cruising behaviour and drivers are not necessarily well informed about parking costs, even when they claim to be familiar with these costs. We also demonstrate that the on-street parking premium could be much larger than our common assumptions and a significant contributor to the increased cruising time. Failing to reflect the premium factor in parking pricing will depreciate the effectiveness of pricing-based strategies to mitigate the cruising for parking issue.

Building waste accounts for over half of the solid waste generated worldwide and has an environmental impact on all stages of the building process, including raw material extraction, manufacturing, transportation, construction and disposal. The recycling and re-use of Construction and Demolition (C&D) waste in Australia is currently below optimal levels and the industry faces ongoing barriers to improvement. Ideally, the industry needs to put greater attention on innovative on-site waste capture and segregation practices, including on-site processing technologies that offer significant benefits, particularly in reducing transport requirements and associated environmental impacts. In order to establish a starting point for empirical research into this topic area, this paper outlines the results of an early review of the literature about on-site waste management innovation and proposes a conceptual framework to be used to investigate the behavioral intentions influencing relevant innovation decisions in building construction projects. To interpret the behavioral dynamics of project-based organizations within the C&D waste management innovation system, a novel conceptual framework is proposed that integrates two key behavioral decision-making theories; Innovation Diffusion Theory (IDT) and Theory of Planned Behavior (TPB). The proposed conceptual framework provides a sound basis for a large scale empirical study of on-site waste management innovation adoption on Australian building projects.

This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.