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The concept of third-party logistics service provider (3PLSP) has been considered as an essential organizational philosophy to achieve profits. The purpose of this paper is to analyze and examine the contextual relationship among the critical success factors (CSF) of 3PLSPs practices in the cement manufacturing industry.

In this paper, the total 20 critical selection criteria with nine processes for the 3PLSPs, of an Indian cement manufacturing industry have been identified through an exhaustive literature review and opinions of the experts i.e. academics and industries. Interpretive ranking process (IRP) methodology has been presented to find out the rankings of the individual criteria and the mutual influence in the selection process.

The proposed model establishes the dominance of relationship among identified criteria, which plays a vital role in the 3PLSPs selection process which are experience in similar product, quality of management, information technology capacity, flexibility in operation and delivery, compatibility with the users.

An empirical research approach has not been used to collect primary data to rank different criteria for effective 3PLSPs implementation in the Industry. In this paper, an example of Indian cement industry is presented to show the real world applicability of the proposed model.

This model would help a decision maker to decide the issues related to a selection of 3PLSPs. The third party service provider comprises the use of external companies who controls and delivers logistic activities. The paper discusses very practical issues in an analytical manner, using the case base method.

The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).

In this study, the interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for enablers. Also, the interpretive ranking process (IRP) was used to analyse and rank enablers with reference to performance variables. For the ISM approach, a structural self- integration matrix was developed with the help of experts’ suggestions and opinions. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship amongst enablers. A total of nine experts were chosen for collecting the primary data in which seven experts belong to the industry and two experts were academicians. The dominant relationship amongst the enablers was analysed through IRP modelling.

A total of 11 enablers were identified for the purpose of this study. The model shows that “leadership and commitment by management”, “human resource management”, “customer relation management”, “supplier relation management” and “information technology system” are the most significant enablers for lean implementation in Bulgarian SMEs as these are positioned at the bottom levels in ISM model. MICMAC analysis shows that five enablers fall in the independent factor, two enablers in linkage factor and four enablers in the dependant factor while there is no enabler in the autonomous factor. ISM and IRP models show that “continuous improvement” is an essential enabler for the successful implementation of lean in Bulgarian SMEs. This study also helps to explain the comparative analysis of ISM and IRP, which indicates that IRP is a more robust modelling approach than ISM, as it incorporates the relationship of enablers with performance variables.

ISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study.

This study supports the professionals/experts to prioritise and manage enablers at strategic and tactical levels while implementing lean manufacturing practices in Bulgarian SMEs. The models developed in the study will be helpful for practitioners to understand and analyse the interdependence of enablers for lean manufacturing implementation.

This study helps to identify and prioritise enablers that affect lean manufacturing adoption using ISM and IRP approaches. Literature shows that numerous authors have used the ISM approach but the use of IRP approach is limited. The models were developed in the study, totally dependent on data collected from the experts to ensure their real-life validity.

Risk management in defence aircraft industry has considerable interest among academics and practitioners. The purpose of this paper is to develop interactions among risk factors dimensions (RFDs) and inspect the importance relationship among the performance measures in Indian aircraft industry and, finally, understand the effect of involvements provided by the managerial team on risk reduction process.

An extensive literature review was carried out to identify 26 risk parameters and 13 performance measure indices relevant for an aircraft industry. Survey method was used to obtain the importance of these parameters and measures. Further, these factors are grouped into five risk dimensions based on the brain storming session by the project managers. Initially, Risk factors for defense aircraft industry (RFDs) analyzed by Interpretative structural model (ISM) to know the contextual relationship among the RFDs and then applied Interpretive ranking process (IRP) to inspect the pre-eminence relationship among them. Finally, SD is applied to understand the effect of involvements provided by the managerial team on risk reduction process.

Government policy and legal RFDs has emerged as the key driving RFDs. In IRP modelling, technology RFD has emerged as more influential RFD which is the more relevant factor with respect to performance measure indices and this result is supported by detailed sensitivity analysis of system dynamic model.

The outcomes of this research can help project management team to identify the high severity risk factors which need immediate risk reduction/mitigation action.

Firms have been adopting lean manufacturing to improve their business performances. However, they are facing failures or less success in implementation, mainly due to lack of understanding in relating the lean practices (LPs) from the required performance measures perspective. In view of the lack of research and the importance of understanding them, the purpose of this paper is to prioritize LPs.

As LPs are scattered in the literature and a variety of performance measures are used, an extensive literature review is first carried out to identify the LPs and performance measures. The blend of interpretive structural modeling and interpretive ranking process interpretive tools is adopted in establishing the contextual relationship among LPs and then ranking them based on the performance measures. A three-dimensional priority matrix is proposed for better explanation of the results.

The proposed framework can help firms better understand LPs and their levels of importance in lean implementation.

The involvement of lean experts may produce some bias in evaluating the LPs.

The proposed framework can help practitioners to develop an industry-specific road-map for the result-oriented LP implementation. Based on the area of performance to be improved, practitioners can prioritize LPs for implementation.

This is the first study that provides a comprehensive review of LPs available in the literature and prioritizes them in accordance with performance with interpretive tools.

The manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.

The barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.

The impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”

The ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.

This study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.

The purpose of this paper is to employ an integrated approach of interpretive ranking process (IRP) and system dynamics (SD) for modelling the key risk factors for a typical construction project.

The risk parameters and performance measures applicable in the construction industry have been identified through extensive literature review and discussions with experts from the construction industry. Based on the literature review, a questionnaire was designed and 64 responses were considered. The list of 20 risk parameters and 32 performance measures relevant for a construction industry is reduced to five risk factors and five performance measure factors using factor analysis. IRP modelling is employed to examine the contextual relationships among risk factors and to rank them with respect to performance measure factors. Subsequently, the results of IRP model were utilised as inputs to SD analysis. The SD analysis is conducted for two models, namely, risk factor model and risk variable model to understand the impact of interventions offered by project management team on risk reduction and mitigation.

The developed IRP model shows that the risk factor dimension “construction management” has a high likeliness to occur during the construction phase.

The research demonstrates an application of proposed approach for a typical construction environment and hence the results cannot be generalised.

This research addresses real life complexities in construction project by modelling critical risk factors using an integrate approach of IRP and SD. The proposed approach would facilitate project managers to devise appropriate risk mitigation strategies for a construction project.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

The purpose of this paper is to report a study on analysis of barriers for cyber-physical system (CPS) adoption in small and medium enterprises (SMEs).

In Industry 4.0 scenario, Indian SMEs are struggling to bring their manufacturing processes in line with large manufacturing sector. CPS is considered as the backbone of Industry 4.0, and its implementation in SMEs will make significant changes pertaining to manufacturing automation. However, due to the lack of a proper CPS implementation strategy, SMEs face many challenges in its adoption. Hence, this study identified 18 possible barriers and seven performance measures pertaining to CPS adoption in Indian SMEs. Interpretive ranking process (IRP) is used to develop the contextual relationships among CPS barriers. IRP process include structured step-by-step matrix-based approach in which dominance among various alternatives is determined using performance measures developing a structured ranking model.

The developed IRP model revealed that CPS barriers “Lack of skilled manpower (CPSB2)” and “Lack of robustness with respect to environmental conditions in automotive environments (CPSB7)” are the most significant barriers (top two) hindering CPS adoption in SMEs.

In the present study, barriers for CPS adoption has been analyzed. In future, barriers for adopting other Industry 4.0 technologies could be analyzed.

The present research work is one of the few studies which analyzed CPS barriers in SMEs and provided improvement suggestions to the most significant barriers for its smooth adoption. The managerial and practical implications have been derived.

The analysis of barriers for CPS adoption in SMEs is the original contribution of the authors.

Effective cost performance is a crucial criterion measuring successful project management in public-housing projects. This paper aims to analyse the vital underlying factors surrounding the successful cost management process (CMP) outcomes in public housing projects (PHPs).

The research was conducted in three stages. The first stage consisted of a detailed literature review to document success factors affecting cost performances and management. In stage two, brainstorming sessions were undertaken with construction experts knowledgeable in cost management practices and have been involved in PHPs. These sessions were used to refine those success factors for the PHPs settings and define their criticality with respect to the CMP stages using interpretive ranking process. In stage three, focus group sessions were performed to validate the interrelationships of the contextualised critical success factors.

The top three most critical factors for successful implementation and outcomes at all CMP stages in PHPs settings were found to relate to competencies, team qualities and collaborative practices of the project team. Early contractor involvement and effective construction planning and management also emerged relevant to the process.

Government project departments, project managers and construction organisations (consultants and contractors) need to commit and mandate continuous development of cost management competencies for all professionals engaged in PHPs. Channels supporting team integration and collaborative practices between design and construction teams are required to increase the likelihood of successful project cost management practice and outcomes in PHPs.

The research has developed a factor-process relationship model that can be used to improve and evaluate the efficacy of CMP implementation in PHP settings.

Activities on direct value chain directly add value to the products/services delivered to the customers. This value addition can be further enhanced by taking up flexibility initiatives on these direct value chain activities. The purpose of this paper is to identify flexibility initiatives on the direct value chain and carry out their valuation.

Since different value addition criteria (i.e. benefits and costs) may be both tangible and intangible, an interpretive valuation based on multi-criteria framework would be desirable. The paper deploys the efficient interpretive ranking process (IRP) for this purpose. It uses total interpretive structural modeling (TISM) to derive weights of criteria based on their respective driving power. The paper also makes a methodological contribution to assess transitive dominance in IRP based on transitivity check as used in the modified TISM process.

The paper uses a multi-criteria valuation to examine the proposition that the flexibility initiatives will add a higher value as we go downstream in the value chain. The flexibility initiatives linked with marketing such as product upgradation and switching, customized services and dynamic pricing are found to be most value adding in character.

The main limitation of this study is that it is generic in nature and need to be replicated in multiple case situations. The methodology proposed can be utilized for specific case analysis for flexibility valuation on the direct value chain.

The practitioners may be able to use the proposed method of TISM–IRP with improvements in real-life applications. The proposed multi-criteria valuation is interpretive in nature and can be utilized by practicing managers in group settings even if they do not have complete data.

The strategy and operations researchers will find promise in the methodology to investigate and prioritize the initiatives planned to enhance flexibility in different value chain activities. The researchers on multi-criteria decision making will find the methodological enhancement proposed in terms of graphically deriving the transitive dominance to be useful in other applications as well.