Systematic Framework Research Articles

A review of Industry 5.0: from key facets to a conceptual implementation framework

PurposeThe purpose of this study is to review the different facets associated with Industry 5.0 (I5.0) and propose a conceptual framework to boost the applicability of this novel technological cum social aspects within industrial organizations for improved organizational sustainability.Design/methodology/approachThis research work adopted a bibliometric analysis that encapsulates a quantitative set of tools for bibliometric and bibliographic information. This study uses the database of Scopus to acquire data related to different facets of I5.0. The study implies a different spectrum of terms to reach the final corpus of 91 articles related to I5.0. Furthermore, a conceptual define, measure, analyze, improve and control (DMAIC)-based framework based on different literature findings is proposed and validated based on the input of experts from different parts of the world.FindingsThe results indicate that I5.0 is still in its infancy. The wider applicability of I5.0 demands comprehensive theoretical knowledge of different facets of this new paradigm and the development of a framework to adopt it on a larger scale. Organizations that are in the race to adopt I5.0 face major challenges related to the digitization of processes along with well-defined cyber-physical systems and the lack of a dedicated framework to execute I5.0. Furthermore, the result also suggests that manufacturing industries are more ready to adopt I5.0 practices as compared to service industries, which can be attributed to well-defined technological measures available in manufacturing settings.Originality/valueTo the best of the authors’ knowledge, this is one of the first studies that explore different know-how and challenges and provides a holistic view of I5.0 by providing a systematic adoption framework.

A Family Therapy Case Study on Family Dynamics Associated with the Truancy of a Middle School-Aged Child in South Korea

ABSTRACT This study examined a family therapy case of an adolescent with truancy to explore family dynamics associated with the adolescent’s development of truancy. The adolescent was a 14-year-old Korean male who had been truant for over a year in South Korea. His family involved in the therapy included the adolescent, his 45-year-old father, 44-year-old mother, 17-year-old sister, and 11-year-old younger brother. The parents sought therapy to address their son’s truancy issues. Using therapy logs and transcriptions, we employed a narrative case study to understand the family dynamics and therapeutic interventions. The identified characteristics of family dynamics were as follows: First, both parents had formed a negative internal working model and dysfunctional coping style due to their family-of-origin experiences. Second, the parents’ internal working model and coping style had a significant impact on the client’s development of his internal working model and coping patterns. Third, the client experienced unresolved emotions from the family at school, contributing to his truancy. The findings have implications for using the family systemic framework in addressing truancy, highlighting the interconnectedness of family dynamics and their impact on adolescent behavior.

Analysis of the Brand Internationalization Status and Development Environment of Chinese Enterprises

Driven by the wave of economic globalization in the 21st century, brand internationalization has become an important strategic choice for the enterprise and even the national level. With the internationalization of the market, the transnational of enterprises, the multinational capital and the intensification of competition, the brand has become a key indicator to measure the economic strength of a country or region. Although Chinese enterprises have cost and product advantages in the international market, their brand advantages are relatively weak, which leads to the limited image of Chinese products in overseas markets, and faces intellectual property challenges and dumping charges. To meet this challenge, the Chinese government has included independent innovation and brand building as the focus of the 11th Five-Year Plan since 2005, with the aim of enhancing international competitiveness. However, Chinese enterprises still face many problems in the process of brand internationalization, including the lack of brand strategy, the lack of understanding of the importance of brand internationalization, and the lack of grasp of development models and methods. At present, the theoretical research of brand internationalization has not yet formed a systematic framework, and there is a relative lack of systematic research on enterprise brand internationalization. Moreover, the practical history of Chinese enterprises in this field is relatively short, which provides a broad space for theoretical research and practical exploration. This paper aims to provide theoretical reference and strategic guidance for Chinese enterprises to enhance their brand competitiveness in the international market through in-depth study of the theory and practice of brand internationalization. Through the elaboration of the relevant theory of brand internationalization, the analysis of the development environment of Chinese brand internationalization, and the construction of the development strategy and mode of enterprise brand internationalization, this paper discusses the support system of brand internationalization development, in order to provide systematic theoretical support for the road of brand internationalization of Chinese enterprises.

Multi-Omics Integration Analysis Pinpoint Proteins Influencing Brain Structure and Function: Toward Drug Targets and Neuroimaging Biomarkers for Neuropsychiatric Disorders.

Integrating protein quantitative trait loci (pQTL) data and summary statistics from genome-wide association studies (GWAS) of brain image-derived phenotypes (IDPs) can benefit in identifying IDP-related proteins. Here, we developed a systematic omics-integration analytic framework by sequentially using proteome-wide association study (PWAS), Mendelian randomization (MR), and colocalization (COLOC) analyses to identify the potentially causal brain and plasma proteins for IDPs, followed by pleiotropy analysis, mediation analysis, and drug exploration analysis to investigate potential mediation pathways of pleiotropic proteins to neuropsychiatric disorders (NDs) as well as candidate drug targets. A total of 201 plasma proteins and 398 brain proteins were significantly associated with IDPs from PWAS analysis. Subsequent MR and COLOC analyses further identified 313 potentially causal IDP-related proteins, which were significantly enriched in neural-related phenotypes, among which 91 were further identified as pleiotropic proteins associated with both IDPs and NDs, including EGFR, TMEM106B, GPT, and HLA-B. Drug prioritization analysis showed that 6.33% of unique pleiotropic proteins had drug targets or interactions with medications for NDs. Nine potential mediation pathways were identified to illustrate the mediating roles of the IDPs in the causal effect of the pleiotropic proteins on NDs, including the indirect effect of TMEM106B on Alzheimer's disease (AD) risk via radial diffusivity (RD) of the posterior limb of the internal capsule (PLIC), with the mediation proportion being 11.18%, and the indirect effect of EGFR on AD through RD of PLIC, RD of splenium of corpus callosum (SCC), and fractional anisotropy (FA) of SCC, with the mediation proportion being 18.99%, 22.79%, and 19.91%, respectively. These findings provide novel insights into pathogenesis, drug targets, and neuroimaging biomarkers of NDs.

The Impact of Environmental Public Opinion Pressure on Green Innovation in Construction Enterprises: The Mediating Role of Green Corporate Image and the Regulatory Effect of Market Competition

Due to growing public concern over environmental preservation and the growing development of Internet information communication platforms, media coverage of corporate environmental issues can exert certain environmental public opinion pressure (EPOP) on enterprises and influence their behaviors. However, the current study of EPOP on the influence mechanism of corporate green innovation (CGI) has not yet formed a systematic and comprehensive theoretical analysis framework. Therefore, based on legitimacy theory and stakeholder theory, this paper explores the impact mechanism and role boundary between EPOP and CGI based on the data from 328 valid questionnaires of construction enterprises of the Chengdu–Chongqing Dual City Economic Circle using hierarchical regression analysis. The findings of the research indicate that EPOP can affect construction company green innovations positively, green corporate image (GCI) plays a partial mediating effect in the relationship between EPOP on CGI; market competition (MC) negatively moderates the relationship between EPOP and CGI, in addition, MC negatively regulates the intermediary effect of GCI in the relationship between EPOP and CGI. The findings of the study serve as theoretical support and decision-making reference to promote Chinese construction enterprise’s transition to green innovation and improve environmental governance level.

A systematic framework for assessing social vulnerability to flood for integrated flood risk management: A case study in Metro Manila, Philippines

Assessing social vulnerability to floods (SVF) is a crucial component of integrated flood risk management, especially in flood-prone regions such as Metro Manila in the Philippines. This study presents a holistic framework to assess SVF, based on susceptibility, exposure, and resilience factors while recognizing its multi-dimensional, multi-attribute, and context-dependent nature. The assessment was applied to three cities of Metro Manila: Marikina, Parañaque, and Manila. Indicators were systematically identified using deductive and hierarchical approaches, and factor indices were derived using a combined Simple Additive Weighting and Analytic Hierarchy Process, while the SVF index was estimated using the vulnerability relationship of the factors. The results exhibit a strong positive correlation with historical social flood damages and robustness across weight and normalization variations, with Marikina being the most vulnerable, followed by Parañaque and Manila. The city-level vulnerability profiles highlight salient determinants such as high population exposure in Parañaque, a relatively high population of susceptible social groups in Marikina, and significant disparity in flood control projects among the cities. Scenario analyses underscore the efficacy of flood countermeasures that reduce exposure and increase resilience. This study offers valuable insights and practical guidance for developing effective disaster reduction plans and policies in the study areas and similar regions by identifying disparities in vulnerability and understanding local conditions and drivers.

MR imaging for preoperative characterization of pelvic adhesions: role in diagnosis and surgical planning.

Pelvic adhesions are nonanatomic connections between organs and normal peritoneal surfaces that develop secondary to a maladaptive inflammatory response to tissue insults. Comprised of fibrous tissue, adhesions can result in the distortion of operative dissection planes, which can complicate the establishment of abdominal access in patients undergoing surgery, prolong the length of surgery, and increase the risk of injury to bowel and other structures if involved by extensive adhesive disease. This can adversely impact patient outcomes by increasing the risk of surgical complications including bleeding, infection, and prolonging postoperative length of stay. Literature on the characterization of adhesions with imaging is limited and a systematic framework for evaluating adhesive disease on cross-sectional imaging of the pelvis does not currently exist. In this review, we discuss the MR imaging features of pelvic adhesions, highlighting unique teaching cases in which surgical exploration was significantly complicated by the presence of adhesive disease. We will also review the correlation between MR imaging and intraoperative findings in these cases. A proposed standardized framework for the detection and characterization of adhesions on pelvic MRI will be reviewed with multiple imaging examples. Identification and characterization of pelvic adhesive disease on preoperative imaging provides radiologists with an opportunity to inform the referring clinician of their presence, potentially improving outcomes and the quality of patient care.

A Study on the Optimization of Water Jet Decontamination Performance Parameters Based on the Response Surface Method

The substrate that adheres between the teeth of the traveling track plate during the operation of a deep-sea polymetallic nodule mining vehicle affects the driving performance, so this study aimed to investigate the effect of the water jet on the cleaning and decontamination performance of the track under different conditions. An optimization design method based on response surface methodology (RSM) is proposed. Based on the Box–Behnken design, the optimization variables of jet pressure, jet target distance, and impact angle, and the target response of jet strike pressure on tracks, were selected, and the numerical simulation method was combined with the response surface method to establish the regression model of the response of each optimization variable to the jet strike pressure on tracks and to determine the optimal parameter combinations. The study findings indicate that the primary factor influencing the pressure of the jet striking the crawler is the jet pressure. The hierarchical order of influence on the pressure of the jet striking the crawler, under the interaction of the three factors, is as follows: jet pressure and impact angle, jet pressure and target distance of the jet, and target distance of the jet and impact angle. The maximum pressure of the jet striking the crawler occurs when the jet pressure is 0.983 MPa, the target distance is 0.14 m, and the impact angle is 89.5°. Overall, the proposed design serves as a systematic framework for parameter optimization in the cleaning and decontamination process, and the research method and results provide theoretical references for the optimal design of mining truck desorption efficiency, which is critical for increasing mining efficiency and lowering energy consumption.

Multivariate statistical analysis and bespoke deviation network modeling for geochemical anomaly detection of rare earth elements

Rare earth elements (REEs), a significant subset of critical minerals, play an indispensable role in modern society and are regarded as “industrial vitamins,” making them crucial for global sustainability. Geochemical survey data proves highly effective in delineating metallic mineral prospects. Separating geochemical anomalies associated with specific types of mineralization from the background reflecting geological processes has long been a significant subject in exploration geochemistry. The processing of high-dimensional, non-linear geochemical survey data necessitates a systematic framework to address common issues, including missing values, the closure effect, the selection of appropriate multivariate analysis methods, and anomaly detection techniques in order to detect geochemical anomalies associated with mineral occurrences. The Curnamona Province in South Australia is considered an emerging REE province with significant REE mineralization potential. In this study, we use data from this region to evaluate the performance of a novel machine learning-based framework that incorporates data pre-processing, multivariate statistical analysis, and anomaly recognition to address challenges such as missing data, noise interference, data imbalance and high non-linearity. We utilize lithogeochemical data to map potential greenfield regions of REE mineralization. The primary advantages of our framework lie in its provision of an effective random forest-based data imputation method, utilization of isometric log-ratio transformation to eliminate the closure effect, and reduction of the impact of outliers on data interpretation through robust principal component analysis. Additionally, the framework utilizes a deviation network to learn anomaly scores from complex, non-linear data under imbalanced data conditions, identifying geochemical anomalies associated with REE occurrences by leveraging prior knowledge rather than those caused by data noise or anthropogenic factors. The anomalous areas identified by this framework delineate all known REE deposits and extend to the surrounding regions. Furthermore, a close spatial coupling relationship exists between these strongly anomalous areas and the felsic granite intrusions. The comprehensive workflow for processing geochemical data proposed in this study can effectively address common challenges in the geochemical exploration of critical minerals. The identified geochemical anomalies can provide important clues for subsequent exploration.

Benchmarking produced water treatment strategies for non-toxic effluents: Integrating thermal distillation with granular activated carbon and zeolite post-treatment

The management of produced water (PW) generated during oil and gas operations requires effective treatment and comprehensive chemical and toxicological assessment to reduce the environmental risks associated with reuse or discharge. This study evaluated a treatment train that included a low-temperature thermal distillation pilot system followed by granular activated carbon (GAC) and zeolite post-treatment for processing hypersaline Permian Basin PW. Our study provides a unique and comprehensive assessment of the treatment efficiency considering a targeted chemical scheme together with whole effluent toxicity (WET) tests across four trophic levels regarding aquatic critical receptors of concern (ROC): Raphidocelis subcapitata, Vibrio fischeri, Ceriodaphnia dubia, and Danio rerio. The distillate from the thermal distillation process met various numeric discharge standards for salinity and major ions. However, it did not meet toxicity requirements established by the United States National Pollutant Discharge Elimination System program. Subsequent post-treatment using GAC and zeolite reduced the concentration of potential stressors, including volatile organics, NH3, Cd, Cr, Zn, and Mn in the final effluent to below detection limits. This resulted in a consistent toxicity reduction across all WET tests, with no observable adverse effects for R. subcapitata, C. dubia, and D. rerio (no observed effect concentration >100%), and V. fischeri effects reduced to 19%. This study realizes the feasibility of treating PW to non-toxic levels and meeting reuse and discharge requirements. It underscores the importance of implementing integrated treatment trains to remove the contaminants of concern and provides a systematic decision framework to predict and monitor environmental risks associated with PW reuse.

Selecting appropriate excipients for paediatric dosage form − Paediatric excipients risk assessment (PERA) framework – Part 1

Excipients are often the major component of the formulation that critically affect the dosage form, manufacturing process, product performance, stability and safety. They exert different roles and functions in a dosage form. Selecting excipients with appropriate safety and tolerability is a major hurdle in paediatric formulation development. The suitability of a particular excipient will be dependent on the context of its use with regard to the paediatric age range, acute versus chronic use, and clinical risk–benefit of the disease, active and excipient. Scientists are encouraged to apply the principle of risk–benefit to assess the suitability of excipients to the specific paediatric population. Indicative list of parameters that should be taken into consideration and hierarchy of information sources when assessing the excipients risks is provided by regulatory agencies. However, the approach to be taken and details of how the risk evaluation should be undertaken are lacking. There is a need for a systematic approach to selection of excipients and assessment of the risk of excipient exposure. The Paediatric Excipients Risk Assessment (PERA) framework developed and proposed in this paper provides a structured, systematic decision-making framework via customizable tools and processes that can help to improve the transparency and communications on the selection and justification of use of excipients in a paediatric formulation.

Self-X heterogeneous attributed graph embedding-based product configuration framework for cognitive mass personalization

Cognitive mass personalization (CMP) is a promising manufacturing paradigm; equipped with cognitive capabilities like reasoning, CMP satisfies changeable needs via configuring personalized products at scale. In CMP, knowledge graphs (KGs) are exploited by smart product-service systems (SPSS) to support cognitive configuration/reconfiguration processes. However, the extant KG-enabled SPSSs are built upon fixed configurations and hybrid frameworks due to lacking a graph embedding (GE) model to render cognitive configuration decisions. In fact, GE is scarcely used in SPSS configuration, because it is not only compromised by the heterogeneity of KGs entailed by content-related specifications and complex structures but also influenced by the feature randomness and feature drift problems, which are triggered by accumulative errors and inconsistent objectives due to noisy assignments and different configuration tasks, separately. To address these limitations, a Self-X Heterogeneous Attributed Graph Embedding (SXHAGE) model is proposed in a Self-X architecture, which includes 1) self-attention graph attention networks, 2) a self-adaptive autoencoder, and 3) self-optimizing training objectives, to present heterogeneous data through jointly optimizing heterogeneous attributed entities and relations. A systematic SXHAGE-based configuration framework, in which product family design and configuration recommending are enabled by graph clustering and link prediction, is developed as a continuous updating loop to proactively configure personalized products. A real-world case study, i.e., configure personalized electric clippers via a web-based sustainable configuration platform, is performed to validate the applicability of the proposed framework in the CMP context. Moreover, extensive experiments on the case study dataset demonstrate the superiority of SXHAGE over the state-of-the-art algorithms, e.g., surpassing Deep Neighbor-Aware Embedding (DNENC) by 18 % in F1-score for graph clustering and by 5 % in ROC-AUC for link prediction.

Industrial ecosystems: A systematic review, framework and research agenda

There is confusion surrounding the concept of industrial ecosystems (IEs). This research therefore presents a systematic literature review on the subject of industrial ecosystems and outlines several paths for future research. The paper defines the key characteristics of IEs, identifies three perplexity drivers that contribute to the conceptual ambiguity of IEs, proposes a four-tier integrative IE framework that outlines the core components of IE research, and presents a conceptual model that clarifies how synergetic effects emerge, leading to IE transformation. Articles are categorized into four categories (industrial symbiosis, metabolism, architecture, and orchestration) from which ten propositions are delineated. The study encourages researchers to tap into several areas from the view that this is a broad, but still rather unexplored area of research with high relevance for policy.

An automated framework for material property calibration in loudspeaker simulation model

The shift to virtual meetings, online classes, and remote work has established a new norm, leading to a surge in the use of virtual communication platforms such as Zoom and Microsoft Teams. This shift has increased the demand for high-quality headsets and speakerphones, emphasizing the need for clear, superior audio quality. The process of calibrating material properties typically relies on repetitive simulations guided by experts' intuition, presenting challenges in establishing new Finite Element Models (FEMs) of loudspeakers, as it requires the repeated identification of material property values. We present a systematic framework for calibrating the mechanical material properties of loudspeaker drivers, a crucial prerequisite for developing accurate FEMs of loudspeakers. Specifically, we propose a statistically-driven approach to replace the conventional manual calibration process, which typically relies on multiple simulations guided by expert intuition. Efficient Global Optimization (EGO) is applied to address the expensive optimization problems of loudspeaker simulation. To tackle the curse of dimensionality, the objective function is decomposed into several functions based on effective parameter groups using Global Sensitivity Analysis (GSA) results. The parameters of the FEM are then calibrated to the reference data from the Lumped Parameter Model (LPM) using the decomposed-reduced objective function, providing the calibrated parameters for the loudspeaker simulation. By implementing this novel approach, even individuals without prior knowledge or experience in loudspeaker material properties can effectively and reliably obtain the necessary data for finite element modeling.

A Coherent Analysis of The Lottery by Shirley Jackson Using Segmented Discourse Representation Theory

Shirley Jackson's The Lottery is a powerful narrative widely analyzed for its social, cultural, and literary dimensions. However, the linguistic intricacies of Jackson's work remain underexplored. This study addresses this gap by applying Segmented Discourse Representation Theory (SDRT) to analyze the discourse structure of The Lottery. SDRT, a formal theory of discourse that emphasizes coherence relations, provides a systematic framework for examining how different narrative segments interact to create a cohesive and impactful story. By employing SDRT, this research uncovers the intricate ways in which Jackson's linguistic choices contribute to the story's thematic depth and emotional resonance. This analysis not only enhances our understanding of Jackson's narrative techniques but also demonstrates the applicability of SDRT in literary discourse analysis, offering new insights into the dynamic development of discourse within literary texts.

Practical output regulation of uncertain Euler–Lagrange systems

This paper deals with the problem of robust output regulation of uncertain Euler–Lagrange systems. An internal model controller is synthesized by a systematic framework that considers polynomial mappings of the steady-state trajectory. The closed-loop stabilization is guaranteed by using a descriptor differential–algebraic representation of the system. This methodology allows the controller design problem to be cast as a convex optimization problem subject to linear matrix inequalities. Simulations considering a two-link robotic manipulator illustrate the method.

Regional coordinated development of low-carbon sports industry in China

This study develops a systematic modeling framework, comprising a prediction model, a super-SBM model, and a spatial autocorrelation analysis model, to explore the spatial–temporal evolution tendencies of development efficiency within China's 30 regions in the low-carbon sports industry from 2006 to 2025. This framework aims to provide theoretical insights for the formulation of more targeted policies. Based on the empirical findings, the main conclusions of this study are as follows: (1) The optimal buffer operator grey prediction model demonstrates the highest accuracy among the prediction models examined. (2) The development efficiency curves of the 30 regions exhibit a significant increasing trend from 2006 to 2021, with values generally peaking between 0.4 and 0.6. (3) Notably, the disparity in development efficiency between developed and less developed regions is expected to progressively widen. (4) The development efficiency of the low-carbon sports industry across the 30 regions typically displays high-high clustering and low-low clustering during China's four five-year plan periods. This underscores the importance and urgency of promoting regional coordinated development within the low-carbon sports industry.

An Integrative Review on Cross-Cultural Psychometric Studies of the Fear of COVID-19 Scale.

Background and Purpose: The rapid spread of coronavirus disease 2019 (COVID-19) worldwide prompted global fear and panic among all populations. The Fear of COVID-19 Scale was developed to assess the degree of fear. This review summarizes and synthesizes the revised cross-cultural validation studies of the Revised Fear of COVID-19 Scale to explore the properties of the scale and fear characteristics among different populations. Methods: A systematic literature search was conducted on the electronic databases of PubMed and Scopus. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis framework. Results: The review demonstrated that the Revised Fear of COVID-19 Scale has robust psychometric properties and fear impacts mental health across all study populations. The characteristics of the fear of COVID-19 are associated with specific variables. Conclusion: The Revised Fear of COVID-19 Scale can be used as a screening tool to assess levels of COVID-19 fear among different populations globally.

Tuning equations for sliding mode controllers: An optimal multi-objective approach for non-minimum phase systems

This article proposes an approach to create tuning equations based on optimal multi-objective design specifically for Sliding Mode controllers applied to non-minimum phase processes that can be approximated to a First-Order-Plus-Deadtime class of systems. This is achieved by taking into account various performance criteria, including tracking, controller action, and transient response. The proposed tuning equations aim to achieve a well-balanced trade-off among competing objectives. The paper presents a systematic framework for formulating the multi-objective optimization problem and derives analytical expressions for the tuning parameters based on the desired performance specifications. The effectiveness of the proposed method is demonstrated through simulations in three dynamic processes: a high-order linear system with dominant delay, a high-order plus inverse response system, and a nonlinear process with variable parameters and dominant deadtime. A comparative analysis with an existing SMC tuning technique shows superior performance results. This paper provides valuable information on the optimization procedure for obtaining analytical tuning equations for controllers, offering a promising avenue for improving the performance of control systems in practical applications.

Problematic issues emerging during BIM implementation process in construction organizations

PurposeBuilding information modeling (BIM) is a popular technology in modern construction, but its implementation faces numerous difficulties, which are known as problematic issues of BIM implementation (PIBIs). This study aims to identify and analyze PIBIs based on the perceptions of practitioners in Vietnamese BIM-implemented construction contractors and similar BIM adoption-level countries.Design/methodology/approachThe research is conducted in three stages. After a comprehensive literature review, PIBIs are identified and ranked based on the Delphi method and questionnaire survey. Next, interpretive structural modeling (ISM) is used to provide a hierarchy of system PIBIs. Finally, the driving and dependence power of PIBIs are determined using Fuzzy-Matrice d'Impacts Croisés-Multiplication Appliquée à un Classement (MICMAC) analysis.FindingsThis study evaluates 32 PIBIs for small and medium contractors (SMCs) and 28 PIBIs for large contractors (LCs) in Vietnam. This study also develops a systematic framework for contextual relationships and analyzes the relationships among PIBIs using ISM-Fuzzy MICMAC analysis. The results show that different standards or techniques, modeling software limitations and information management significantly impacted LCs, while a lack of senior leadership support and incompatible software affected SMCs, causing other PIBIs.Originality/valueThis study is among the first attempts to investigate the problematic issues emerging during the BIM implementation process at the organizational level in Vietnam as well as other developing countries. The study results could be considered valuable references for BIM practitioners. Furthermore, this knowledge can enable contractors to avoid problems while adopting BIM, thereby increasing their ability to implement BIM successfully and using critical resources more efficiently.