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The purpose of this paper is to identify and prioritize the lean implementation (LI) barriers in the context of labor intensive Indian ceramic industries through a statistically reliable and validated model.

In this study, LI barriers are identified through a comprehensive review of relevant literature and discussions held with academicians/practitioners. Identified barriers, thereafter, are evaluated with Cronbach's alpha values using a statistical tool. The interpretive ranking process (IRP) methodology is applied for ranking of the barriers with reference to the measurable performance indicators.

The study identified highly relevant barriers of Indian ceramic industries. Further, these barriers were compared with performance measures through a cross-interaction matrix developed in the IRP model. The model highlights the analysis of dominance relationship of different barriers. Moreover, the result shows that top management commitment and leadership is at the top of the model, followed by lack of training opportunity and skills, and resistance to change and adopt innovations indicating their strongest driving power in LI.

This model may enable the firms to understand the LI barriers and come up with sensible implementation program. Further, the correlation results among the barriers will provide insights in mitigating the hurdles of lean manufacturing (LM) implementation in the industries.

This study empirically develops a model through the IRP for the barriers in LM implementation. From the reported literature, it appears that the application of IRP is very rare in ceramic industries in India. The analysis and prioritization of LI barriers may help practitioners to plan strategies to implement lean in a selected domain.

Research on organizational climate has shown a significant upward trend in the recent past. The purpose of the present study is to propose a conceptual model that empirically examines the relationship of dimensions of organizational climate with managerial effectiveness in Indian organizations.

A data set of 245 managers/executives was collected from Indian organizations through a survey instrument. The collected responses were subsequently tested by using structural equation modeling (SEM). Further, the hypothesized model was tested by employing five stages of hierarchical multiple regressions.

The findings suggest that organizational climate dimensions, i.e. organizational process, altruistic behaviour, role clarity and communication, results‐rewards orientation and certain aspects of interpersonal relationships play a significant role in increasing managerial effectiveness.

The results indicate ways in which organizations might develop supportive climates in order to reinforce effectiveness of the organizational members.

The role of organizational climate in employee effectiveness is currently under‐researched in the Indian context. The present study is an earnest effort in this direction to analyse the link between organizational climate and managerial effectiveness.

Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.

This study aims to present comprehensive nonlinear material modelling techniques and simulations of reinforced concrete (RC) beams subjected to short-term monotonic static load using the robust and reliable general-purpose finite element (FE) software ANSYS. A parametric study is carried out to analyse the flexural and ductility behaviour of RC beams under various influencing parameters.

To develop and validate the numerical FE models, a total of four experimentally tested simply supported RC beams are taken from the available literature and two beams are selected from each author. The concrete, steel reinforcements, bond-slip mechanism, loading and supporting plates are modelled using SOLID65, LINK180, COMBIN39 and SOLID185 elements, respectively. The validated models are then used to conduct parametric FE analysis to investigate the effect of concrete compressive strength, percentage of tensile reinforcement, compression reinforcement ratio, transverse shear reinforcement, bond-slip mechanism, concrete compressive stress-strain constitutive models, beam symmetry and varying overall depth of beam on the ultimate load-carrying capacity and ductility behaviour of RC beams.

The developed three-dimensional FE models can able to capture the load and midspan deflections at critical points, the accurate yield point of steel reinforcements, the formation of initial and progressive concrete crack patterns and the complete load-deflection curves of RC beams up to ultimate failure. From the numerical results, it can be concluded that the FE model considering the bond-slip effect with Thorenfeldt’s concrete compressive stress-strain model exhibits a better correlation with the experimental data.

The ultimate load and deflection results of validated FE models show a maximum deviation of less than 10% and 15%, respectively, as compared to the experimental results. The developed model is also capable of capturing concrete failure modes accurately. Overall, the FE analysis results were found quite acceptable and compared well with the experimental data at all loading stages. It is suggested that the proposed FE model is a practical and reliable tool for analyzing the flexural behaviour of RC members and can be used for performing parametric studies.

Despite a large amount of BIM data at the handover stage, it is still difficult to identify and effectively isolate valuable construction supply chain (CSC) data that need to be reliably handed over for operation. Moreover, the role of reconciling disparate data is usually played by one party. The integration of blockchain and BIM is a plausible framework for building a reliable digital asset lifecycle. This paper proposes a BIM single source of truth (BIMSSoT) data model using blockchain for ensuring a reliable CSC data delivery.

This paper utilises a blended methodology, the foundation of which is ingrained in business and management research with elements of information and communication technology (ICT) research wherever required. Knowledge elicitation case studies utilising novel interventions such as a data flow diagram (DFD), taxonomy and entity-relationship diagram (ERD) were used in this paper to develop the BIMSSoT data model. The model was validated using an expert forum, and its technological feasibility was established by developing a proof of concept.

The practical contribution of this research leads to the progression of BIM towards digital engineering to go beyond object-based 3D modelling by building structured and reliable datasets, transitioning from project-centric records to a digital ecosystem of linked databases by utilizing blockchain's potential for ensuring trusted data.

To the best of the author's knowledge, prior to this paper, no research had investigated a detailed data model development leveraging blockchain and BIM to integrate an immutable and complete record of CSC data as another dimension of BIM for operations.

Service quality is an evaluation of how well a delivered service meets customers’ expectations. The purpose of this paper is to provide a reliable scale of measurement for service quality in banks.

The SERVQUAL model was adopted based on a Banking Service Quality (BSQ) model and a two-phase multiobjective optimization model was designed. A structured questionnaire with five-point Likert scale was administered with a 93 percent response rate of 270 sample size. A total of 22 variables were considered based on the BSQ model and the significance of these variables to customers’ satisfaction were investigated. Factor analysis was used to extract the most influential factors on the measure of service quality and four factors were selected namely: they deliver when promised, precision on account statements, queues that move rapidly and sufficient number of ATMs per branch. In order to determine the reliability of the multiple Likert questions in the survey, Cronbach’s α was used indicating a scale reliability of 0.743. Moreover, multiple regression analysis was carried out on the selected factors to design an objective function for the design and evaluation of service quality model. The model design used for benchmarking was done using multiobjective genetic algorithm in MATLAB. Similarly, the model evaluation was done in a java interface using multiobjective particle swamp optimization.

The evaluation results validated the designed model and showed that the factors they deliver when promised and queues that move rapidly are a more reliable scale of measurement for customer’s satisfaction than the factors precision on account statements and sufficient number of ATMs per branch.

The implication of the results is that effectiveness and assurance combined with access is a more significant factor for measuring customers’ satisfaction than tangibles based on the BSQ model.

The introduction of a two-phase optimization model for model benchmarking and evaluation as compared to ordinary factor analysis of the dimension constructs.

This research study aims to develop regular cylindrical pore network models (RCPNMs) to calculate topology and geometry properties of explosively created fractures along with their resulting hydraulic permeability. The focus of the investigation is to define a method that generates a valid geometric and topologic representation from a computational modelling point of view for explosion-generated fractures in rocks. In particular, extraction of geometries from experimentally validated Eulerian smoothed particle hydrodynamics (ESPH) approach, to avoid restrictions for image-based computational methods.

Three-dimensional stabilized ESPH solution is required to model explosively created fracture networks, and the accuracy of developed ESPH is qualitatively and quantitatively examined against experimental observations for both peak detonation pressures and crack density estimations. SPH simulation domain is segmented to void and solid spaces using a graphical user interface, and the void space of blasted rocks is represented by a regular lattice of spherical pores connected by cylindrical throats. Results produced by the RCPNMs are compared to three pore network extraction algorithms. Thereby, once the accuracy of RCPNMs is confirmed, the absolute permeability of fracture networks is calculated.

The results obtained with RCPNMs method were compared with three pore network extraction algorithms and computational fluid dynamics method, achieving a more computational efficiency regarding to CPU cost and a better geometry and topology relationship identification, in all the cases studied. Furthermore, a reliable topology data that does not have image-based pore network limitations, and the effect of topological disorder on the computed absolute permeability is minor. However, further research is necessary to improve the interpretation of real pore systems for explosively created fracture networks.

Although only laboratory cylindrical rock specimens were tested in the computational examples, the developed approaches are applicable for field scale and complex pore network grids with arbitrary shapes.

It is often desirable to develop an integrated computational method for hydraulic conductivity of explosively created fracture networks which segmentation of fracture networks is not restricted to X-ray images, particularly when topologic and geometric modellings are the crucial parts. This research study provides insight to the reliable computational methods and pore network extraction algorithm selection processes, as well as defining a practical framework for generating reliable topological and geometrical data in a Eulerian SPH setting.

Contemporary organizations face challenges when they have an increasing need for trust, and yet there are decreasing opportunities for the development of interpersonal trust. Thus, the organizations cannot rely only on that and there is a need for complementary forms of organizational trust. Vanhala et al. (2011) developed the scale for measuring impersonal trust. The purpose of this study is to validate the scale in terms of discriminant and nomological validity as well as to test generalizability.

The validities and generalizability is tested on two samples from two industries in Finland: a forest company (411 respondents) and ICT company (304 respondents). Confirmatory factor analysis and structural equation modelling are used.

The scale represents both discriminant and nomological validity. Furthermore, the scale is generalizable in different industries.

A more holistic approach to organizational trust is proposed, and the scale for the impersonal element of the organizational trust is validated.

This paper validates the scale for the less studied impersonal element of organizational trust. To manage and develop organizational trust, all of its dimensions should be measured. The scale validated allows the measurement of the impersonal dimension, and the more refined measure also makes it possible to focus development efforts on certain operational areas.

The scale validated represents a step forward toward the reliable measurement of organizational trust. To the best of the researcher’s knowledge, this is the first study to show that previously developed scale is valid and generalizable.

The paper aims to identify the most supply chain resilient company suitable for the customized preferences of partner firms in the context of the Chinese supply chain framework during the COVID-19 pandemic.

A hybrid multicriteria model, i.e. Fuzzy Analytical Hierarchy Process (AHP), was used to assign weights to each criterion, which was subsequently analyzed by three approaches, namely Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory), and Evaluation Based on Distance from Average Solution (EDA), to rank the top ten companies in descending order of supply chain resilience. Further, sensitivity analysis is performed to identify the consistency in ranking with variation in weights. The rankings are validated by a novel Ensemble Ranking algorithm and by supply chain domain experts.

The rankings suggest the company “China Energy Construction Group Tianjin Electric Power Construction Co., Ltd” is the most feasible and resilient company, presenting interesting findings to partner firms, and Bosch is the least reliable supply chain company of the ten firms considered, thus presenting interesting findings to partner companies.

“Crisis Management Beforehand” is most critical in the current pandemic scenario. This implies that companies need to first prioritize taking proactive steps in crisis management followed by the need to minimize the “Expected impact of pandemic.” Performance factors also need to be regulated (sales, supply chain rank and financial performance) to maintain the company's overall reputation. Considering the consistent performance of the China Energy Construction Group Tianjin Electric Power Construction Co., Ltd., it is recommended as the most reliable supply chain firm to forge strategic partnerships with other supply chain stakeholders like suppliers and customers. On the other hand, Bosch is not recommended as a supply chain reliable company and needs to improve its crisis management capabilities to minimize the pandemic impact.

The paper aims to identify the most supply chain resilient company suitable for the customized preferences of partner firms in the context of the Chinese supply chain framework during the COVID-19 pandemic. The rankings suggest the company “China Energy Construction Group Tianjin Electric Power Construction Co., Ltd” is the most feasible and resilient company, presenting interesting findings to partner firms, and Bosch is the least reliable supply chain company of the ten firms considered, thus presenting interesting findings to partner companies.

The purpose of this paper is to validate the Press Ganey Questionnaire (PGQ) (Bahasa Melayu version) using Hospital Universiti Sains Malaysia (HUSM) patients.

This cross-sectional study comprised 252 patients visiting HUSM. Patients were selected using the convenience sampling method. The PGQ (Bahasa Melayu version) had three main factors: during your visit; your care provider and overall assessment. Data were analyzed using the structural equation modeling.

The exploratory factor analysis resulted in item reduction from 21 to 17, which contained four factors with eigenvalues greater than 1. Meanwhile, confirmatory factor analysis results showed that data fitted the model: χ²/df at 1.764, comparative fit index at 0.952, Tucker–Lewis index at 0.941 and root mean square error of approximation at 0.073. The average variance extracted value for the four factors was greater than 0.50, which indicated that PGQ convergent validity was met. Overall, PGQ produced good reliability with composite reliability score equals to 0.966. Four factors were reclassified as “during your registration,” “hospital staff attitude,” “doctor’s attitude” and “overall assessment.”

Patient satisfaction is an important and frequently used indicator for measuring healthcare quality; hence, a validated and reliable instrument is important for measuring patient satisfaction that leads to healthcare service quality assessment.

Validated PGQ provides some useful information for doctors, medical assistants, nurses and staff in the emergency department to help them become more prominent and efficient in their role as healthcare providers.

Validated PGQ will help healthcare providers to deliver the best and exceptional care toward emergency patient, and thus improve their quality of work life. The findings in this study can be used as a guide or as baseline data for further research in this area.

The PQG (Bahasa Melayu version) was confirmed as a reliable and valid instrument for measuring patient satisfaction. This research is the first PGQ validation study in Southeast Asia, specifically focusing on Malaysian respondents.