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Several studies have addressed the use of four-dimensional (4D) building information modeling (BIM) for construction management. However, the automation of the processes for generating 4D models and their integrated use with Location-Based Planning and the Last Planner® System is not well discussed. Therefore, this paper aims to develop a method for automating the generation and use of 4D BIM models integrated with Location-Based Planning and Last Planner® System supporting project control cycles.

The research strategy adopted was Design Science Research. The automated method for using the 4D models was developed and refined in two residential building projects in Brazil, along with 31 meetings and involving 11 direct users. The assessment of the proposed method focuses on four constructs: the impact of process automation, the impact on the identification and assessment of site progress and the planning process, ease of adoption and utility of the proposed method.

The results of this paper indicated increased adherence between planned and executed through an automated method for using the 4D models. The established routines enabled automating the link between the planning levels and the three-dimensional (3D) model, providing a more agile and updated data source and achieving 92.8% of user satisfaction regarding the deadline and frequency of delivery of the 4D model reports. Moreover, this study identified the relationships between the processes of the method proposed and Digital Models.

The primary scientific value achieved in this study is creating a method for automating processes and simplifying steps for the generation and use of 4D BIM models in the production planning and control cycles during the construction phase.

This paper analyzes and illustrates the spatial distribution of publications in international urban planning journals from 2010 to 2020.

The study employs the Biblioshiny bibliometrix package in R to analyze 44,123 articles from 95 international planning journals. To conduct the spatial scientometric analysis, we adopted the United Nations’ geoscheme focusing on three geographical scales: country, subregion, and region. Collaboration patterns at the country and subregional levels were examined using the VOSviewer tool.

The study found evidence of a spatial polarization of urban planning scholarly knowledge production. Scholars based in the United States and the United Kingdom consistently published at higher rates than any other country in our data set. The region producing the largest number of publications was Europe, consisting of 39.92% of the total publication count. However, urban planning scholars from the Global South authored only 20.96% of planning publications from 2010–2020. Centralization of planning research is also evident within each region and subregion. As such, both the Global North and the Global South should not be framed as homogenous entities and spatial patterns of knowledge production should not be generalized. The analysis also established the emerging role of Northern America as a major collaborator in inter-country and inter-subregional research collaborations. Co-authorship patterns indicate low intra-regional collaboration in planning research, except for Europe.

This article argues that a culture of exclusivity may be occurring in urban planning publication production. By highlighting the spatial disparities in knowledge production, we emphasize the need to examine the structural and institutional barriers that exclude urban planning knowledge emerging from the peripheries in international planning journals.

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?

This study aims to investigate four internal (organisational structure, quality of information technology, business strategy and market orientation) and two external (competition intensity and perceived environmental uncertainty) contextual factors affecting the use of production planning and control accounting techniques (PPC), as well as the impact of PPC usage on organisational competitiveness.

Seven major PPC techniques were investigated, namely: attribute costing, lifecycle costing, quality costing, target costing, value-chain costing, activity-based costing and activity-based management. By deploying a multi-informant strategy, a structured questionnaire was used to gather survey data from 129 senior accounting, finance and production personnel of publicly quoted manufacturing companies in Nigeria.

The results, using structural equation modelling, show that market orientation is the strongest determinant of PPC usage. The inability of competition intensity and perceived environmental uncertainty to notably affect PPC usage suggests that external environmental pressure to use PPC is weak. Although PPC can engender organisational competitiveness, their interactive usage yields optimal results.

The study contributes to knowledge by: (i) presenting evidence that although PPC techniques can engender organisational competitiveness, it is their interactive usage that yields optimal results; (ii) empirically demonstrating that contextual factors influence PPC usage in line with the contingency theory; and (iii) validating the diffusion of innovation theory that organisations will typically deploy PPC techniques because of their relative advantage of improving organisational competitiveness.

This paper aims to show the impact of applied visual management (VM) on performance in logistics operations in the construction industry.

A case study was conducted at a branch of an international company located in Poland on VM implementation in the transport and storage of this firm. Active research was used to include the outlook of top management on the implementation and use of VMs.

This study demonstrates how VM is an effective way to improve performance in the studied logistics functions. The complex nature of the effect is revealed not only in warehouse and transport operations but also in handling operations, improving operational planning and specializing warehouse teams.

Organizational culture, work discipline and value system in the group of production and warehouse workers is of importance in implementing and efficiently using VM resources. Using a VM is complex.

This study aimed to identify the determinants of farmers' participation in agricultural information-sharing digital groups and their impacts on farm performance.

Primary data of the 2015/2016 crop year collected from 175 cattle farmers were analyzed using descriptive statistics and econometric models. Farmers who had smartphones and participated in social groups/applications, especially those created to exchange agricultural information, were considered adopters of the technology.

A Poisson hurdle model showed that farmers' decision to participate in agricultural information-sharing digital groups is determined by schooling, age (negative effect) and use of tools for planning production. The intensity of participation is affected by risk propensity, interaction with specialist advisors, use of tools for planning production and participation in cooperatives. The authors also found empirical evidence that farmers' participation in agricultural information-sharing digital groups positively affects farm income per hectare.

The results of this study are important for accelerating the diffusion of low-cost digital technologies, which are powerful tools for improving farmers' sharing and access to valuable information in real time and in locations far from urban areas.

To the best of the authors’ knowledge, this is the first empirical analysis of the adoption and impacts of agricultural information-sharing digital groups/applications by Brazilian cattle farmers. The diffusion of simple digital technologies is important for reducing heterogeneity and increasing the efficiency of cattle production.

Modular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.

We develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.

The experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.

To the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.

Business Process Reengineering (BPR) eliminates non-value-added (NVA) and essential non-value-added (ENVA) waste through radical process redesign to improve organizational operations. Comprehensive research integrating BPR tools is needed to understand their benefits for manufacturing firms. This research presents an integrated BPR-simulation framework tailored to the manufacturing sector to maximize process improvements and operational excellence.

The BPR design methodology adopts a systematic, multi-stage approach. The first phase involves identifying a specific improvement process aligned with BPR's core objectives. This phase analyses and redesigns workflows to optimize task sequences, roles, and stakeholder interactions while eliminating redundancies and inefficiencies via Workflow Process Reengineering. Visual process mapping tools, including VSM and simulation, pinpoint areas of waste, delay, and potential enhancement. The second phase follows the workflow analysis and aims to improve efficiency and effectiveness by redefining roles, rearranging tasks, and integrating automation and technology solutions. The redesigned process undergoes evaluation against key performance indicators to ensure measurable improvements are achieved. The final phase validates the proposed changes through simulation models, assesses the impact on key performance metrics, and establishes the necessary infrastructure for successful implementation. The proposed model is empirically validated through a case study of a leading apparel company in Vietnam, confirming its effectiveness.

The findings reveal that NVA activities are being eliminated, and ENVA activities in key departments are significantly reduced. This yielded a substantial improvement, reducing 25 out of 186 combined ENVA and NVA operations in the sewing facility, involving a decrease of 15 ENVA operations and the removal of 10 NVA operations. Consequently, this led to an 8.5% reduction in the proportion of ENVA operations, accompanied by a complete 100% elimination of NVA activities.

The single case study limits generalizability; thus, expanded implementation across diverse manufacturing sub-sectors is required to establish validity and broader applicability of the integrated framework.

The experimental results highlight the proposed model's effectiveness in optimizing resource utilization and its practical implementation potential. This structured BPR methodology enables organizations to validate, evaluate, and establish proposed process changes to enhance operational performance and productivity.

Research and Development (R&D) plays a significant role in promoting social and economic development in cities. In urban planning practice, a lack of evidence-informed policies and misguided research efforts can undermine national and local development efforts. This research aims to outline the state of academic research in urban planning and propose a tentative urban planning research agenda in Jordan. Specifically, the study identifies emerging research areas within postgraduate urban planning research in Jordan, examines the extent to which current research activities align with national research priorities, and determines research areas of top priority for Jordanian cities.

The research employs a mixed-method approach using content analysis to analyze academic urban planning research in Jordan and the Delphi method targeting Jordanian urban planning experts to identify research areas that should be prioritized in Jordan within the next five years.

The findings indicate that while urban design and housing, neighborhoods, and community development were the dominant fields of study in postgraduate urban planning research, planning experts identified transportation and land use planning as research areas of top priority for the next five years. The results also suggest that national research priorities lack specificity and offer little guidance for researchers in complex and multifaceted scientific disciplines, such as urban planning.

This research lays the foundations for developing a comprehensive and feasible urban planning research agenda that is responsive to the diverse needs of communities and cities across Jordan. It offers three propositions to guide future knowledge production in urban planning: emphasizing research activity in priority areas, decentralizing research activities, and fostering inter/transdisciplinary research linkages. To the best of the author's knowledge, this study is the first to propose an urban planning research agenda in Jordan.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.