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The purpose of this study is to identify the critical readiness factors (CRFs) that mainly affect the implementation of Lean Six Sigma (LSS) in an organization and their interactions, and to develop a model that allows the management to assess the Lean Implementation Readiness Level.

The methodology is separated into two main parts: the literature review and the assessment model development. In the literature review, the main CRFs and their interactions for LSS implementation in Scopus Data Base were identified. The second part of the methodology is the model development. It was built on a stepwise framework that considers the relations among the CRFs and their importance. Moreover, it was used fuzzy-based linguistic variables given by the experts working in the company to consider the actual performance rating of each CRF. The model has been validated in the healthcare sector in nine hospitals.

From the model application, it is possible to note that the most frequent level among the nine hospitals interviewed is “Average Ready”. Also, the most extreme level of readiness occurred ones while the most extreme level of not readiness never occurred. Results show that in 78% of the cases, there would have been a high probability of implementation failure. Also, it was possible to identify for each hospital if the CRFs are good, if they are weak and need to change or if another factor needs to be improved before it and what this factor is.

This work proposes a new methodology that eliminates the negative aspects and limitations of the total interpretive structural modeling methodology and the fuzzy logic approach currently applied to evaluate the LSS readiness of a company. The present methodology lies in the fact that it provides a solution not only by defining the weak CRFs but also by giving an indication of priority as it identifies the weak antecedent factors that inhibit the preparedness of the depending factors.

The purpose of this paper is to determine the critical factors (CRFs) of IS/ISO/IEC 17025:2005 laboratory accreditation and indicators of the performance (IOPs) in the testing/calibration laboratories. The impact of accreditation on the performance is analyzed using the level of presence of critical factors that can be used to benchmark the best practices in the accredited testing and calibration laboratories.

A questionnaire is designed on the basis of an extensive literature review on laboratory accreditation and performance. Based on the responses from pilot study, the developed instrument is tested for its unidimensionality, reliability and validity. Multiple regression analysis is carried out to analyze the impact of critical factors on the IOPs.

The findings reveal that the six distinct critical dimensions of laboratory accreditation (which are the independent variables) have a significant impact on the performance of the accredited testing/calibration laboratories. The performance is measured by the dependent variables which are the IOPs. The customer satisfaction, employee satisfaction, laboratory performance, image of the laboratory, the number of increased customers and loyalty of the existing customers are highly influenced by the accreditation which in turn improves the performance to gain the competitive advantage.

Contribution to research is in the area of laboratory accreditation and the performance measurement by the development of a comprehensive instrument to analyze the Laboratory Quality Management System. The results are dependent on the number of respondents who are the quality/technical managers.

This instrument would enable the accredited laboratories to analyze their performance through the feedback from the quality/technical managers to gain credibility and to continually improve and benchmark the quality management system in alignment with the quality policies.

This paper proposes an instrument to measure and benchmark the performance of the accredited testing and calibration laboratories.

The purpose of this paper is to identify and then evaluate perceived risk factors influencing variability between contract sum and final count, and to develop a fuzzy risk assessment model for evaluating the overall impact of established critical risk factors impacting on variability between contract sum and final account in government-funded construction projects. Construction projects are characterised by risk factors that significantly impact on variability between the contract sum and final account.

A research approach integrating questionnaire survey, mean scoring ranking and principal component factor analysis (PCFA) methods was adopted to evaluate and classify the critical risk factors. A fuzzy synthetic evaluation method was sequentially applied to compute the overall risk impact (ORI) of eight critical risk factors’ impact on variability between contract sum and final account.

Initial results showed that eight critical risk factors have high impact on variations between contract sum and final account, namely (in order): project funding problems, underestimation of quantities, variations by client, change in scope of works, inadequate specification, change in design by client, defects in design and unexpected site (ground) conditions. PCFA produced two factor solutions: “professional-related factors” and “client factors”. The fuzzy model further showed that the ORI is 5.48, indicating that these risk factors have a high impact on variability between contract sum and final account in public construction projects. The client factors have a very high impact (5.59), while the professional-related factors indicated a high impact (5.41) on project cost variability.

A practical model is proposed to evaluate the key risks associated with cost overruns in public projects. By giving effective and sustained attention to these factors, variability between contract sum and final account, a common situation in Ghana, can be controlled to achieve cost savings in public infrastructure projects.

This study aims to evaluate the key risk factors inherent in public–private partnership (PPP) power projects in Ghana and further determine the critical risk factors affecting both the public and private sectors in PPP power projects.

Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical risk factors of PPP. Purposive and snowball sampling techniques helped obtain experts for the Delphi survey. Mean score ranking, factor analysis, Cronbach α coefficient and Kendall’s concordance were used for analysis. The probability of occurrence and severity of each risk factor were computed to obtain the risk impact.

From the list of 67 risks, 37 risk factors were deemed to be critical. The five topmost risk factors were: delay payment on contract, private investor change, political risks, fluctuating demand of power generated and public opposition. Principal component analysis grouped the risk factors into seven major themes.

This study develops an authoritative risk factor list for PPP power projects, which reflects both sector and country conditions for prioritizing and mitigating risk factors. Delphi approach adopted in this study can be used by future studies in similar environments where PPP is novel and expert respondents scarce.

This paper aims to evaluate the risk factors and determines the overall risk level (ORL) of public-private-partnership (PPP) power projects in Ghana using fuzzy synthetic evaluation methodology (FSEM).

In this paper review of literature led to the development of a 67-factor risk list which was ranked by experts and industry practitioners through a questionnaire survey.

These factors were grouped into principal risk factors (PRFs) using component analysis and they served as the input variables for fuzzy analysis. The seven components were: Contract and Payment risks, Environmental risks, Financial and Cost risks, Legal and Guarantee risks, Operation risks, Socio-Political and Performance risks (SPR) and Tender and Negotiation risks. Study showed that the ORL of Ghanaian PPP power projects is high implying they are risky to both the public and private sectors. Fuzzy analysis also confirmed SPR as the most critical principal factor.

This study is significant and demonstrates that fuzzy methodology can be used as a useful risk evaluation tool and risk assessment framework for private investors, policy makers and public sector.

This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.

The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.

The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.

The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.

This study aims to investigate the interactive network of risk factors in the construction and preparation project of gas condensate storage tanks in the presence of sanctions.

First, this paper determines and weighs the project goals using the stepwise weight assessment ratio analysis method. Then, this study identifies and categorizes the project risks and form the network of the project risk factors based on the weight of the project goals by using interpretive structural modeling and decision-making trial and evaluation laboratory techniques.

The results of the current work divide the risks of such projects into five financial, technical, managerial and contractual, social and environmental and political categories. The analyzes indicate the complicated risk network and the cause-and-effect interactions between the risks. The findings identify the financial and political risk clusters as the most effective category and select the technical, managerial and contractual and social and environmental risk clusters as the most affected categories. The technical risk has the least important among the others under the sanction conditions.

This paper model the domino effect of the risk factors considering the complicated interactions and the cause-and-effect relations in a network. Moreover, this study discusses the importance of the risk factors in oil and gas megaprojects in the presence of sanctions. Finally, this paper applies the proposed approach to a real case study in the field of gas projects.

Prefabricated construction has proven to be superior in terms of affordability and sustainability over the years. As a result of sustainable production, prefabricated housebuilding has evolved into a distinct industry reliant on supplier companies acting as supply chains (SCs) for housing projects. These companies' performance is critical to the successful implementation of prefabricated housebuilding technologies. However, in comparison to those choosing manufacturing as a strategy in other industries, the life span of these companies, providing innovative housing solutions, is relatively short. This is due to critical factors influencing the performance, but the inter-relationship of the performance dimensions is more significant. This study establishes the inter-relationship of the companies involved in house building with steel prefabricated housebuilding technologies.

The most recent factors were extracted from the literature. The relationships were developed using the interpretive structural modeling (ISM) method with the input from industry experts, and the driving factors were determined using the Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) technique.

Critical performance factors were classified according to performance dimensions, ranked and classified based on driving and dependence power. The inter-relationships among the performance dimensions of time, quality, cost, delivery, features and innovation were determined. Key performance strategies were proposed for prefabricated housebuilding companies involved in manufacturing and/or assembly of steel products.

This study established the interrelationship of performance dimensions for prefabricated house building (PHB) companies to develop strategies against critical challenges to remain competitive in the housing market. Previous research had not looked into interrelationship among the performance dimensions. The proposed performance strategies are applicable to supplier organizations using steel prefabricated technologies in similar markets around the world.

This study aims at investigating the impact of the perceived importance of critical cultural readiness factors (CRFs) is on perceived importance of Lean Six Sigma (LSS) technical critical success factors (CSFs) in UK manufacturing sector.

A survey questionnaire through a multiple embedded case study was conducted. The study involves surveying people in the manufacturing firms followed by non-parametric Kruskal–Wallis test to study the relationships.

It was found that the people's perception towards impact of CRFs on technical CSFs of LSS projects is different depending upon each CRF, demographic factors and technical CSFs. This means that particular CRFs need to be prioritised to address LSS technical CSFs.

The study fills the research gap in investigating the perception of people towards inter-relationship of cultural or soft CSFs of LSS and technical or hard CSFs of LSS in manufacturing firms. Nevertheless, the authors suggest further multi-case study analysis covering different manufacturing fields as future studies.

The study is crucial for managers financially to be ready to invest on a successful LSS project and it helps them to diagnose the cultural causes of failure in a more timely way and effectively.

This is a preliminary study focussing on analysing inter-relationship between perceived importance of soft readiness factors and perceived importance of implementing success factors as a missing jigsaw in the current literature.

The purpose of this paper is to identify the major public–private partnership (PPP) risks in infrastructure projects in Afghanistan and explain the extent to which extent the identified risks can shed light on the PPP implementation study in general.

Initially, 78 risks were identified through considering international laws and regulations, criteria for using PPP in developing and underdeveloped countries, and case studies. Later, 23 of the more important risks were determined, ranked and classified into five main groups.

Finally, these risks were adapted with some investigations conducted in the PPP field. Although some of the risks identified in this survey are unique to Afghanistan, this research can be used to develop the application of PPP generally.

PPP is one possible solution to finance infrastructure projects. However, there are a lot of risks, which make this method inefficient in Afghanistan. Therefore, identifying the risks of PPP can play an important role in improving the infrastructures of Afghanistan.