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Energy analysis (EA) within a building information modelling (BIM) enables consistent data integration in central repositories and eases information exchange, reducing rework. However, data loss during information exchange from different BIM uses or disciplines is frequent. Therefore, a holistic approach for different BIM uses enables a coherent life cycle information flow. The life cycle information flow drives the reduction of data loss and model rework and enhances the seamless reuse of information. The latter requires a specification of the EA key performance indicators (KPIs) and integrating those in the process.

The paper presents a set of KPIs extracted from the developed EA process maps and interviews with expert stakeholders. These KPIs stem from the literature review and link to the benefits of EA through industry expert review. The study includes (1) development and validation of EA process maps adjusted to requirements from different stakeholders. (2) KPIs aligned with the EA process map, (3) identification of the drivers that can facilitate life cycle information exchange and (4) opportunities and obstacles for EA within BIM-enabled projects.

This paper depicts a viable alternative for EA process maps and KPIs in a BIM-enabled AEC design industry. The findings of this paper showcase the need for an EA within BIM with these KPIs integrated for a more effective process conforming to the current Open BIM Alliance guidance and contributing towards sustainable life cycle information flow.

The limitation of the research is the challenge of generalising the developed EA process maps; however, it can be adjusted to fit defined organisational use. The findings deduced from the developed EA process map only show KPIs to have the ability to facilitate adequate information flow during EA.

The AEC industry will benefit from the findings of this primary research as the industry will be able to contrast its process maps and KPIs to those developed in the paper.

This paper benefits the societal values in EA for the built environment in the design stages. The subsequent life cycle information flow will help achieve a consistent information set and decarbonised built environment.

The paper offers a practical overview of process maps and KPIs to embed EA into BIM, reducing the information loss and rework needed in the practice of this integration. The applicability of the solution is contrasted by consultation with experts and literature.

This chapter explores the traditional and evolving practice of preservation. Traditional preservation practices are traced throughout history. Current practice is described as a foundation from which to understand evolving practices. Traditional preservation has historically focused on tangible assets that take a tangible form we can all see and touch. The traditional practices are compared to the evolving practices of knowledge and intangible resources. The chapter examines why, what, how, when, where we preserve, and who preserves to understand the transition in progress today. The authors make the case that shifting the traditional focus from preserving for the past and evidentiary reasons to preserving for the future to support business challenges is crucial. The authors also tie the need to refocus on historical impediments and challenges to knowledge use and reuse in practical business environments.

The built environment is taking enormous leaps towards its digitalization. Computer-aided tools such as building information modeling (BIM) are found in the forefront of this evolution, playing a critical role in creating the foundations for the upcoming development of smart low-carbon cities. However, the potential of BIM is still untapped – links will need to be created among the available and forthcoming methodologies under one integral operational system. The purpose of this paper is to present an integrated BIM-based life cycle-oriented framework for achieving sustainable constructions at the pre-construction phase. The developed framework represents an example of the approaches that the construction industry will need to adopt to integrate the different tools under an integrated smart city context.

The methodological approach follows the development of four same-volume different-configuration three-dimensional BIM designs, which are coupled with life cycle assessment (LCA) tools for establishing sustainable building design.

The results of this paper indicated that the choice of building design and shape can play a significant role in reducing the embodied energy and embodied carbon of buildings, achieving a reduction of up to 15% compared to a reference building of same volume and gross floor area.

The originality of this paper is found in its approach application by coupling three-dimensional BIM models with LCA data, the use of reinforcement detailing in an nD BIM study and the employment of country-specific LCA databases.

In the last decades, various building information modeling–life cycle assessment (BIM-LCA) integration approaches have been developed to assess the environmental impact of the built asset. However, there is a lack of consensus on the optimal BIM-LCA integration approach that provides the most accurate and efficient assessment outcomes. To compare and determine their accuracy and efficiency, this study aimed to investigate four typical BIM-LCA integration solutions, namely, conventional, parametric modeling, plug-in and industry foundation classes (IFC)-based integration.

The four integration approaches were developed and applied using the same building project. A quantitative technique for evaluating the accuracy and efficiency of BIM-LCA integration solutions was used. Four indicators for assessing the performance of BIM-LCA integration were (1) validity of LCA results, (2) accuracy of bill-of-quantity (BOQ) extraction, (3) time for developing life cycle inventories (i.e. developing time) and (4) time for calculating LCA results (i.e. calculation time).

The results show that the plug-in-based approach outperforms others in developing and calculation time, while the conventional one could derive the most accuracy in BOQ extraction and result validity. The parametric modeling approach outperforms the IFC-based method regarding BOQ extraction, developing time and calculation time. Despite this, the IFC-based approach produces LCA outcomes with approximately 1% error, proving its validity.

This paper forms one of the first studies that employ a quantitative and objective method to determine the performance of four typical BIM-LCA integration solutions and reveal the trade-offs between the accuracy and efficiency of the integration approaches. The findings provide practical references for LCA practitioners to select appropriate BIM-LCA integration approaches for evaluating the environmental impact of the built asset during the design phase.

Supply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.

The proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.

The findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.

There are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.

1. Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

2. Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

3. Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

4. Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.

Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.

The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.

This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.

Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

Michael Buckland's works have spanned theoretical, historical and practice-oriented foci and genre. This article focuses on some of his theoretical-historical works that span over 20 years, which demonstrate a reading and critique of European Documentation in terms of what has been called “Documentality.” This turn to a philosophy of information called “Documentality” marks the moment of “neo-documentation.” This article surveys this moment in Buckland's works by reading his articles “Information as Thing,” “What is a ‘Document’?”, and “Documentality Beyond Documents.” It shows the transition from Documentation as a philosophy of information as representation to Documentality as a philosophy of information as function and performance. Some concepts and works of Bruno Latour are used to illuminate this transition from Documentation to Documentality. Implications and further research directions are discussed at the end.

Conceptual and historical analyses.

The article follows a neo-documentalist transition in Buckland's works in the thinking of documents from an Otletian representationalist epistemology (“Documentation”) to a functionalist and performative epistemology (“Documentality”) for documents.

This is a conceptual work on a limited corpus in Buckland's oeuvre. It has a limited discussion of Documentality in the works of other writers, namely the works of Bernd Frohmann and Maurizio Ferraris.

The article points to historical shifts in the study of documents in Library and Information Science.

Documentality critically and materially studies documents in sociotechnical information management systems and elsewhere.

This work highlights the importance of the above works and the importance of the neo-documentalist perspective of Documentality.

This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.

This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.