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Article
Publication date: 1 February 2021

Ibrahim Yahaya Wuni, Geoffrey Qiping Shen and Robert Osei-Kyei

Prefabricated prefinished volumetric construction (PPVC) is a game-changing construction method that transforms the fragmented site-based construction of buildings into an…

Abstract

Purpose

Prefabricated prefinished volumetric construction (PPVC) is a game-changing construction method that transforms the fragmented site-based construction of buildings into an integrated production, integration and assembly of value-added volumetric building components. Where circumstances merit, the effective implementation of PPVC leverages significant gains in time, cost, quality, productivity and sustainability performance of construction projects. As PPVC is increasingly becoming mainstream, it is imperative to identify the critical success criteria (CSC) for measuring PPVC project success. The purpose of this study is to identify, rank and benchmark the CSC for measuring PPVC project success.

Design/methodology/approach

This study adopted a quantitative research design where the potential CSC for PPVC projects were evaluated. A comprehensive literature and pilot expert review identified 18 CSC for measuring PPVC project success. Based on a questionnaire survey of international PPVC experts, the 18 CSC were analyzed and prioritized using mean score analysis and weighting function.

Findings

Based on mean index assessment, the top five CSC for PPVC projects were identified as adherence to project schedules, meeting project quality specification, meeting safety requirements, client and owner satisfaction and cost savings and profitability. Further analysis grouped the 18 CSC into six principal success criteria (PSC), comprising time performance, cost performance, quality performance, environmental and safety performance, stakeholder satisfaction and supply chain performance. Based on weighted analysis of the six PSCs, quality performance, time performance and environmental and safety performance obtained the highest weights.

Research limitations/implications

The research results are limited by the following limitations. First, although adequate, the sample size was relatively smaller. Second, the generalized analysis overlooked the geospatial sensitivities of the CSC.

Originality/value

The results constitute the first exclusive quantitative ranking and prioritization of the CSC for PPVC projects. The outputs of this study will enable practitioners to reliably and accurately evaluate the performance levels of PPVC projects. A framework of the CSC for measuring the success of PPVC projects was developed.

Details

Journal of Financial Management of Property and Construction , vol. 26 no. 2
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 25 November 2021

Fábio Henrique de Souza, Luiz Octávio Gavião, Annibal Parracho Sant'Anna and Gilson B.A. Lima

This study aims to develop a risk prioritization process using failure mode and effect analysis (FMEA) in association with composition of probabilistic preferences (CPP) and…

Abstract

Purpose

This study aims to develop a risk prioritization process using failure mode and effect analysis (FMEA) in association with composition of probabilistic preferences (CPP) and weighting the risk analysis criteria. It seeks to develop decision-making considering the fast response necessary to achieve project objectives in complex scenarios, such as the pandemic of COrona VIrus Disease 19 (COVID-19).

Design/methodology/approach

After identifying the risks, the prioritization process was applied to a project in the oil and gas area, in which a focus group assessed these risks. This evaluation took place employing traditional FMEA, FMEA with CPP by axes considering four points of view and FMEA with CPP by weighted sum with the use of a multicriteria method to weight the criteria. These approaches were compared to understand their differences and benefits, with a flow chart being developed, consolidating the procedure.

Findings

The methodologies that showed the greatest benefits were FMEA with CPP by axes PO (progressive-optimistic) and by weighted sum. Essentially, this was mainly related to the interrelationship between risks and to the importance of prioritization.

Originality/value

This procedure can consider company's views on what is critical and the interrelationship between risks. It provides a clear segmentation of what should and should not be prioritized. It was also developed in a practical case, showing a possible alternative to support fast responses in decision-making.

Details

International Journal of Managing Projects in Business, vol. 15 no. 4
Type: Research Article
ISSN: 1753-8378

Keywords

Article
Publication date: 20 August 2018

Liping Wang, Pu Zhang, Pei Zhang, Rongbo Li, Yanke Zhang and Yueqiu Wu

Public–private partnership (PPP) projects are increasingly significant in many countries. The purpose of this paper is to assess the impact of critical success factors (CSFs) on…

Abstract

Purpose

Public–private partnership (PPP) projects are increasingly significant in many countries. The purpose of this paper is to assess the impact of critical success factors (CSFs) on PPP projects and comprehensively consider the interrelations and interaction among dimensions and factors to achieve a better understanding of PPP project management.

Design/methodology/approach

An evaluation index system for PPP projects such as the presented case study is proposed based on a literature review and a survey. Then, interpretative structural modeling is used to transform the CSFs dimension into a multi-level hierarchical model to reflect the driven-dependency relation of each dimension; the fuzzy analytic network process model optimized by moment estimation theory is used to investigate the impact of CSFs by considering their internal impact.

Findings

Regarding the project used as the case study, the driving force and dependence for driving layer and dependent layer are determined. Moreover, in driving layer, efficient and well-structured payment mechanism is the most important CSF if considering the internship and interaction among CSFs, and efficient and well-structured payment mechanism and good governance provide most positive interaction; in dependent layer, population of beneficiaries is the most important CSF if considering the internship and interaction among CSFs, and public client’s satisfaction provides most positive interaction.

Originality/value

This paper developed an evaluation model to explore the interrelationships of dimensions and factors and then determine the impact of CSFs. The model propose in this paper relaxes the independence assumptions of traditional methods and is more in line with reality; besides, weighting method is optimized to obtain more objective and reasonable evaluation results. Through an empirical study, the validity of the model has been verified; therefore, the study can help project stakeholders better understand the CSFs and further improve project performance.

Details

Engineering, Construction and Architectural Management, vol. 25 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 20 February 2020

Ignacio Contreras

Data envelopment analysis (DEA) is a mathematical method for the evaluation of the relative efficiency of a set of alternatives, which produces multiple outputs by consuming…

Abstract

Purpose

Data envelopment analysis (DEA) is a mathematical method for the evaluation of the relative efficiency of a set of alternatives, which produces multiple outputs by consuming multiple inputs. Each unit is evaluated on the basis of the weighted output over the weighted input ratio with a free selection of weights and is allowed to select its own weighting scheme for both inputs and outputs so that the individual evaluation is optimized. However, several situations can be found in which the variability between weighting profiles is unsuitable. In those cases, it seems more appropriate to consider a common vector of weights. The purpose of this paper is to include a systematic revision of the existing literature regarding the procedures to determine a common set of weights (CSW) in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure. The discussion and findings of this paper provide insights into future research on the topic.

Design/methodology/approach

This paper includes a systematic revision of the existing literature about the procedures to determine a CSW in the DEA context. The contributions are classified with respect to the methodology and to the main aim of the procedure.

Findings

The discussion and findings of the literature review might insights into future research on the topic.

Originality/value

This papers revise the state of the art on the topic of models with CSW in DEA methodology and propose a systematic classification of the contributions with respect to several criteria. The paper would be useful for both theoretical and practical future research on the topic.

Details

Journal of Modelling in Management, vol. 15 no. 4
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 23 May 2023

Minggong Zhang, Xiaolong Xue, Ting Luo, Mengmeng Li and Xiaoling Tang

This study aims to establish an evaluation method for cross-regional major infrastructure project (CRMIP) supportability. The focus is to identify evaluation indicators from a…

Abstract

Purpose

This study aims to establish an evaluation method for cross-regional major infrastructure project (CRMIP) supportability. The focus is to identify evaluation indicators from a complexity perspective and develop an evaluation model using qualitative and quantitative methods. Case studies are carried out to verify the reliability of the evaluation model, thereby providing theoretical and practical guidance for CRMIP operations and maintenance (O&M).

Design/methodology/approach

Guided by the idea of complexity management, the evaluation indicators of CRMIP supportability are determined through literature analysis, actual O&M experience and expert interviews. A combination of qualitative and quantitative methods, consisting of sequential relationship analysis, entropy weighting, game theory and cloud model, is developed to determine the indicator weights. Finally, the evaluation model is used to evaluate the supportability of the Hong Kong–Zhuhai–Macao Bridge (HZMB), which tests the rationality of the model and reveals its supportability level.

Findings

The results demonstrate that CRMIPs' supportability is influenced by 6 guideline-level and 18 indicator-level indicators, and the priority of the influencing factors includes “organization,” “technology,” “system,” “human resources,” “material system,” and “funding.” As for specific indicators, “organizational objectives,” “organizational structure and synergy mechanism,” and “technical systems and procedures” are critical to CRMIPs' O&M supportability. The results also indicate that the supportability level of the HZMB falls between good and excellent.

Originality/value

Under the guidance of complexity management thinking, this study proposes a supportability evaluation framework based on the combined weights of game theory and the cloud model. This study provides a valuable reference and scientific judgment for the health and safety of CRMIPs' O&M.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 3 September 2020

Qinqin Zeng, Wouter Beelaerts van Blokland, Sicco Santema and Gabriel Lodewijks

Current literature presents limited measurement methods of quantifying manufacturers' performance with environmental concerns. The purpose of this paper is to construct a company…

Abstract

Purpose

Current literature presents limited measurement methods of quantifying manufacturers' performance with environmental concerns. The purpose of this paper is to construct a company performance index for benchmarking motor vehicle manufacturers (MVMs) with environmental concerns.

Design/methodology/approach

Methods of constructing the index include regression analysis, a modified linear method for normalizing variables and a geometric mean for aggregating variables into a single index IMVM (index for MVMs). A case study is conducted in 12 MVMs from 2008 to 2017. A sensitivity analysis with the simple additive weighting method is performed to analyze how different aggregation methods affect the final value. The index IMVM is assessed through a benchmark with three existing indices.

Findings

Three realistic considerations are identified from MVMs, based on which proper and transparent methods are chosen to construct the IMVM. The construction of the index IMVM has been assessed through a benchmark against the methodologies of three other indices. The results indicate that the new measurement is feasible and effective for MVMs to measure their company performance from an environmental perspective.

Practical implications

The construction of the index IMVM can support policymakers with accurate statistics for decision-making. As a response to current imperative climate policies, this paper raises awareness of CO2 emissions in vehicles' production. For statistical organizations and stakeholders in the investment world, this paper provides available and reliable statistics for trend analysis of different MVMs.

Originality/value

A new method is designed for constructing a company performance index for MVMs. Three environmental variables are identified based on literature, their environmental impact as well as their data availability from public documents. A ranking by manufacturer with environmental concerns is generated. This index can contribute with available statistics and useful insights toward decision-making.

Details

International Journal of Productivity and Performance Management, vol. 70 no. 7
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 17 April 2023

Ping Li, Zhipeng Chang and Wenhe Chen

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making…

Abstract

Purpose

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

Design/methodology/approach

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

Findings

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

Originality/value

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 27 March 2023

Mikko Rönkkö, Nick Lee, Joerg Evermann, Cameron McIntosh and John Antonakis

Over the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems…

2335

Abstract

Purpose

Over the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems with the technique but have had little impact on its use in marketing research practice. This study aims to present some of these criticisms in a reader-friendly way for non-methodologists.

Design/methodology/approach

Key critiques of PLS are summarized and demonstrated using existing data sets in easily replicated ways. Recommendations are made for assessing whether PLS is a useful method for a given research problem.

Findings

PLS is fundamentally just a way of constructing scale scores for regression. PLS provides no clear benefits for marketing researchers and has disadvantages that are features of the original design and cannot be solved within the PLS framework itself. Unweighted sums of item scores provide a more robust way of creating scale scores.

Research limitations/implications

The findings strongly suggest that researchers abandon the use of PLS in typical marketing studies.

Practical implications

This paper provides concrete examples and techniques to practicing marketing and social science researchers regarding how to incorporate composites into their work, and how to make decisions regarding such.

Originality/value

This work presents a novel perspective on PLS critiques by showing how researchers can use their own data to assess whether PLS (or another composite method) can provide any advantage over simple sum scores. A composite equivalence index is introduced for this purpose.

Details

European Journal of Marketing, vol. 57 no. 6
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 25 January 2013

Ilker Murat Ar, Coşkun Hamzaçebi and Birdogan Baki

The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the…

Abstract

Purpose

The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the teaching performance of Turkish BSs. The final objective is to test the functionality and applicability of the model.

Design/methodology/approach

This study presents a ranking approach based on grey relational analysis (GRA). While evaluating the BSs, data were collected for 19 Turkish BSs in terms of five main criteria such as OSS score; Number of faculty members; Number of students per faculty member; the mean of KPSS score; and the standard deviation of KPSS score. In the analysis, three weighted methods were integrated into the GRA in order to weight the criteria.

Findings

According to this result, the main factor influencing the teaching performance of Turkish BSs is the OSS score. This study can also confirm that the results obtained from the ranking orders using the proposed methods are reliable and these results can help decision makers to identify the best alternative.

Research limitations/implications

In order to provide benchmarking data more effectively, in future, it would be helpful to collect data from both foundation and state universities with a research focus. Moreover, as an interesting suggestion for future research, fuzzy environment may be further integrated into the framework of GRA.

Originality/value

In contrast to prior research, this study makes comparisons based on the scores of national exams instead of different bibliometric indicators. Furthermore, there are no studies which have used GRA and these weighted methods as combined in education sector.

Details

Grey Systems: Theory and Application, vol. 3 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 3 April 2018

Davood Gharakhani, Abbas Toloie Eshlaghy, Kiamars Fathi Hafshejani, Reza Kiani Mavi and Farhad Hosseinzadeh Lotfi

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU…

Abstract

Purpose

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU selects the best weighting schemes to obtain maximum efficiency for itself. Therefore, using different sets of weights leads to many different efficient DMUs, which makes comparing and ranking them on a similar basis impossible. Another issue is that often more than one DMU is evaluated as efficient because the selection of weights is flexible; therefore, all DMUs cannot be completely differentiated. The purpose of this paper is to development a common weight in dynamic network DEA with a goal programming approach.

Design/methodology/approach

In this paper, a goal programming approach has been proposed to generate common weights in dynamic network DEA. To validate the applicability of the proposed model, the data of 30 non-life insurance companies in Iran during 2013-2015 have been used for measuring their efficiency scores and ranking all of the companies.

Findings

Findings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure.

Originality/value

The proposed model delivers more knowledge of the common weight approaches and improves the DEA theory and methodology. This model makes it possible to measure efficiency scores and compare all DMUs from multiple different standpoints. Further, this model allows one to not only calculate the overall efficiency of DMUs throughout the time period but also consider dynamic change of the time period efficiency and dynamic change of the divisional efficiency of DMUs.

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