Interpretive Ranking Process Research Articles

Prioritizing industry 4.0 technologies (I4.0T) through an interpretive ranking process (IRP): a design and manufacturing perspective

Prioritizing industry 4.0 technologies (I4.0T) through an interpretive ranking process (IRP): a design and manufacturing perspective

The food industry supply chain: Synergy of environmental orientation and collaboration in implementing circularity

AbstractCircularity within supply chains can be realized through the seamless integration of ecological concerns into business strategies, coupled with stakeholder collaboration throughout the supply chain. A study of a supply chain aiming for circularity was conducted in a real setting for a renowned multinational company in the food processing industry to explore how environmental orientation shapes collaborative practices. The model was applied to reveal the significance of the circular practices that supply chain members follow within the case company. The interpretive ranking process (IRP) was further applied to rank the stakeholders in the supply chain of this company. Results reveal that raw material suppliers, farmers, customers, and volunteers occupy a significant position in implementing circularity in this supply chain. It is essential to provide incentives to suppliers in order to encourage them to adopt practices that promote circular supply chains. Simultaneously, local communities need to play an active role in implementing effective waste management practices. This case study underscores the critical imperative of nurturing a pro‐environmental mindset while fostering synergetic collaboration among stakeholders, thereby paving the path towards achieving circularity.

Building risk mitigation strategies for circularity adoption in Indian textile supply chains.

Textile industries are among the most polluting and demand urgent management measures to mitigate their negative environmental impact. Thus, it is imperative to incorporate the textile industry into the circular economy and to foster sustainable practices. This study aims to establish a comprehensive, compliant decision framework to analyse risk mitigation strategies for circular supply chain (CSC) adoption in India's textile industries. The Situations Actors Processes and Learnings Actions Performances (SAP-LAP) technique analyses the problem. However, interpreting the interacting associations between the SAP-LAP model-based variables is somewhat lacking in this procedure, which might skew the decision-making process. As a result, in this study, the SAP-LAP method is accompanied by a novel ranking technique, namely, the Interpretive Ranking Process (IRP), which reduces decision-making issues in the SAP-LAP method and aids in evaluating the model by determining the ranks of variables; furthermore, the study also offers causal relationships among the various risks and risk factors and various identified risk-mitigation actions by constructing Bayesian Networks (BN) based on conditional probabilities. The study's originality represents the findings using an instinctive and interpretative choice approach to address significant concerns in risk perception and mitigation techniques for CSC adoption in the Indian textile industries. The suggested SAP-LAP and the IRP-based model would assist firms in addressing risk mitigation techniques for CSC adoption concerns by providing a hierarchy of the various risks and mitigation strategies to cope with. The simultaneously proposed BN model will help visualise the conditional dependency of risks and factors with proposed mitigating actions.

Prioritizing the Key Actors of an Organization for Business Excellence Using the Efficient Interpretive Ranking Process

Flexibilities are involved in the process of decision-making. They offer much freedom of choice in terms of the selection of suitable actors who interact with the dynamic environment of the organization. This paper presents a systematic and holistic approach to ranking key actors responsible for the business excellence of an organization. The study highlights the area where the actors of the organization should focus on achieving desired business excellence. It portrays the outcome in the form that top management is the most influential actor since it is responsible for the formulation of the vision/mission of the organization along with the setting of plant quality targets, cost-saving targets, manpower planning, and policy formulation for energy-saving. Top management is followed by cross-function teams (CFTs) and the government of India (GOI) in terms of interaction with the various processes. The novelty of this case study is that it utilizes qualitative and interpretive tools for the analysis, which does not require much statistical knowledge to produce outcomes, and the results are easy to understand. The reported results are in consensus with the results reported by various studies that are conducted using quantitative tools like Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), total interpretive structural modelling (TISM), etc. that require statistical excellence for the calculation, interpretation, and dissemination of results to the general public and shopfloor employees.

A systematic inquiry of energy management in smart grid by using SAP-LAP and IRP approach

PurposeThe 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.Design/methodology/approachAccording 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.FindingsThis 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.Practical implicationsThe 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.Originality/valueThe 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.

Investigating and modeling interactions among manufacturing barriers due to Covid-19 pandemic: an interpretive ranking process

PurposeThe 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.Design/methodology/approachThe 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.FindingsThe 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.”Practical implicationsThe 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.Originality/valueThis 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.

Impact of transportation on climate change: An ecological modernization theoretical perspective

Among the various climate change causing agents, transportation alone is responsible for 19.2% of the carbon emissions. By proper implementation of various preventive measures, the impact of transportation on climate change can be drastically reduced. It is also necessary to determine the relationship between the transportation factors responsible for creating environmental degradation and causing climate change and to rank them based on the preventive measures impact to deal with them. In this paper, we have identified the transportation factors that affect climate change and the factors related to its preventive measures based on the ‘environment’, ‘sociology’ and ‘modernity’ elements of Ecological Modernization Theory (EMT). Given the context, this study focusses on development of an assessment framework that combines three techniques: Simple Additive Weighting (SAW), Interpretive Structural Modelling (ISM) and Interpretive Ranking Process (IRP).

Exploring the Lean Implementation Barriers in Small and Medium-Sized Enterprises Using Interpretive Structure Modeling and Interpretive Ranking Process

Past research reveals that many lean implementation barriers hinder lean implementation in small and medium-sized enterprises (SMEs). Among many sectors, the manufacturing sector suffers more as it generates more waste while carrying out manufacturing processes. Many manufacturing units make unsuccessful attempts to implement lean principles in their manufacturing systems. Hence, such units must eliminate the prevailing lean barriers to accomplish successful lean implementation. Moreover, the contextual relationship of lean barriers must be studied to understand the effect of such barriers. This paper uses interpretive structural modeling (ISM) to explore lean barriers, their relationships, and their influence on other lean barriers. The present research also reveals the most significant classification of lean barriers into various categories of independent, dependent, autonomous, and linkage using the (MICMAC) Matrice d’Impacts Croisés Multiplication Appliquée á un Classement analysis. ISM and MICMAC together provide relationship modeling and reveal the interrelationship between each lean implementation barrier and its categories, respectively. The ISM model is validated using the Delphi technique. The interpretative ranking process (IRP) is used to rank the barriers. The three significant lean implementation barriers revealed through the IRP include “lack of lean understanding”, “lack of strong quality policy”, and “risk of sustainable practice implementation”. The present research will help practicing managers of SMEs in the manufacturing sector to understand the mutual influence of lean barriers before introducing lean implementation. It is suggested that SMEs work on independent barriers so that dependent barriers can also be overcome with the least amount of resources and effort.

Exploring the Issues in Policy Deployment Using SAP-LAP and eIRP Approaches: An Empirical Case Study

Policy deployment refers to the formulation of policies, their implementations, and reviews. Every organization irrespective of its size and sector involves the process of policy deployment. There exist many factors that affect the process of policy deployment. These factors pose flexibilities that can alter the outcome of a policy. This paper explores the flexibilities in the choice of the factors governing a policy decision. An Indian auto-spare part industry with certain policy issues is selected for theory building. A framework model for solving the policy deployment issues is formulated using an interpretive comparative technique known as situation-actor-process-learnings-actions-performance (SAP-LAP). It is based on the comparative study of contextual relationships within and among its various elements. The contextual relationship within a particular element is presented in the form of a self-interaction matrix and the contextual relationships among the elements are depicted using the cross-interaction matrix. Further, the actors and actions of the framework are ranked using an efficient interpretive ranking process (eIRP) for easy selection and prioritization. The ranks obtained through the efficient IRP model will facilitate the policymakers in the formulation of better decisions and implementation of key policies.

Prioritizing Key Business Actions of an Indian Automobile Industry Using Efficient Interpretive Ranking Process (eIRP)

Prioritizing Key Business Actions of an Indian Automobile Industry Using Efficient Interpretive Ranking Process (eIRP)

An analysis of Industry 4.0 implementation-variables by using SAP-LAP and e-IRP approach

PurposeIn today’s uncertain business environment, Industry 4.0 is regarded as a viable strategic plan for addressing a wide range of manufacturing-related challenges. However, it appears that its level of adoption varies across many countries. In the case of a developing economy like India, practitioners are still in the early stages of implementation. The implementation of Industry 4.0 appears to be complex, and it must be investigated holistically in order to gain a better understanding of it. Therefore, an attempt has been made to examine the Industry 4.0 implementation for the Indian manufacturing organization in a detailed way by analyzing the complexities of relevant variables.Design/methodology/approachSAP-LAP (situation-actor-process and learning-action-performance) and an efficient interpretive ranking process (e-IRP) were used to analyze the various variables influencing Industry 4.0 implementation. The variables were identified, as per SAP-LAP, through a thorough review of the literature and based on the perspectives of various experts. The e-IRP has been used to prioritize the selected elements (i.e. actors with respect to processes and actions with respect to performance) of SAP-LAP.FindingsThis study ranked five stakeholders according to their priority in Industry 4.0 implementation: government policymakers, industry associations, research and academic institutions, manufacturers and customers. In addition, the study also prioritized important actions that need to be taken by these stakeholders.Practical implicationsThe results of this study would be useful in identifying and managing the various actors and actions related to Industry 4.0 implementation. Accordingly, their prioritized sequence would be useful to the practitioners in preparing the well-defined and comprehensive strategic roadmap for Industry 4.0.Originality/valueThis study has adopted qualitative and quantitative approaches for identifying and prioritizing different variables of Industry 4.0 implementation. This, in turn, helps the stakeholder to comprehend the concept of Industry 4.0 in a much simpler way.

Analysis of lean implementation barriers in Indian ceramic industries: modeling through an interpretive ranking process

PurposeThe 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.Design/methodology/approachIn 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.FindingsThe 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.Practical implicationsThis 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.Originality/valueThis 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.

An Intelligent Framework for Analyzing the Feasible Modes of Transportation in Metropolitan Cities: A Hybrid Multicriteria Approach

The paper aims to build a hybrid personalized multicriteria model in the Indian transportation industry to identify the most feasible transport mode suitable for commuters’ customized preferences. A hybrid multicriterion model, i.e., Fuzzy Analytical Hierarchy Process (AHP), was used to compute the criteria weights, which were subsequently analyzed by three approaches, namely, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy TOPSIS, Evaluation Based on Distance from Average Solution (EDA), and Interpretive Ranking Process (IRP). The case of an Indian metropolitan city, Hyderabad, is taken to illustrate the proposed approach. The paper highlights the following transport modes: metropolitan train (unconventional mode) and conventional modes such as the car, public bus transport, and bikes for Hyderabad. Furthermore, sensitivity analysis is performed to identify the consistency in ranking with variation in weights, and the Ensemble Ranking and transportation experts validate the rankings.

Critical success factors for cost management in public-housing projects

PurposeEffective 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).Design/methodology/approachThe 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.FindingsThe 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.Practical implicationsGovernment 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.Originality/valueThe research has developed a factor-process relationship model that can be used to improve and evaluate the efficacy of CMP implementation in PHP settings.

Development of Framework for Lean Implementation: An Interpretive Structural Modeling and Interpretive Ranking Process Approach

Development of Framework for Lean Implementation: An Interpretive Structural Modeling and Interpretive Ranking Process Approach

Critical success factors of lean manufacturing for Indian ceramic industries: Modelling through interpretive ranking process

In India, majority of manufacturing organizations comes under small and medium size enterprises (SMEs) that are recognized as backbone for the economy by contributing a significant amount in gross domestic product (GDP). In the competitive business environment, SMEs are trying to enhance the value of their production and services on decimating the non-productive activities from their manufacturing systems. It has been reported in previous explorations that lean manufacturing (LM) is an approach to recognize and eliminate different forms of waste from the production process, and improve the business performance. Therefore, SMEs has to follow lean manufacturing to ensure sustainable profitability. To optimise the LM implementation benefits, organization/s must see the different success factors thoroughly. So far, critical success factors (CSFs) of lean manufacturing in labour intensive SMEs were not explored systematically. In this study, CSFs for implementing lean are extracted from literature and were analysedand validated after discussion held with relevant industrial experts/academicians. Interpretive ranking process (IRP) technique was employed to observe the relationship amongst the CSFs. To check the interpretations and pair-wise comparison, a dominance system graph for each performance measures was developed. The results revealed that regular training and education for workers, proper selection of lean tools/techniques and low scrap/rework/elimination of waste are the most CSFs for implementing lean in Indian ceramic SME sector.

Modeling the Interactions Among Critical Criteria of a Cellular Manufacturing System

The aim of this article is to investigate the interactions between the critical criteria of implementation of the cellular manufacturing system (CMS). In this article, 15 critical criteria are chosen on the basis of literature review and opinion of experts from the manufacturing industry, which was analyzed for their interactions and dominant relationships using the interpretive structural modeling (ISM) methodology and interpretive ranking process (IRP) methodology, respectively. These distinct modeling approaches have been employed to study the appropriate relationship among the CMS implementation criteria and their ranking considering key performance areas. The study marks is an attempt to fulfill the gap in the literature, as the literature majorly focuses on CMS implementation, but pays no attention to models considering such critical criteria. The ISM model particularly highlighted the importance of employee training over other critical criteria, which will in turn ensure the success of CMS implementation, while the IRP model revealed CAD/CAM as the most important criterion when evaluated against various performance areas. The study, thus, paves a new way for manufacturing organization's management to be aware of critical criteria and analyze those that might be important for the future survival of the organization.

Interdependency analysis of lean manufacturing practices in case of Bulgarian SMEs: interpretive structural modelling and interpretive ranking modelling approach

PurposeThe paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs).Design/methodology/approachIn 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.FindingsA 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.Research limitations/implicationsISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study.Practical implicationsThis 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.Originality/valueThis 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.

Effect of SCF on automobile industry performance during sales promotional schemes

PurposeIn today's competitive market subject to various uncertainties, supply chain flexibility (SCF) arose as a potential weapon to enhance the firm's performance. This paper model the effect of SCF on automobile industry performance during sales promotional schemes (SPS), which has turned out to be one of the most important marketing tools.Design/methodology/approachIn view of the literature and the expert opinion taken from an automobile OEM, the SCFs and performance measures pertaining to the SPS environment have been identified. For the purpose of ranking the SCFs with respect to the performance measures, the Interpretive Ranking Process (IRP) has been applied using the direct contact method as a means for establishing the contextual relationships between SCFs and performance measures and to draw the interpreting reasons behind them.FindingsThe findings of this study along with the validity and stability of the results assessed through the system graphs and sensitivity analysis demonstrate that flexibility at the procurement end followed by the organizational end has the highest impact on the performance of the company during SPS.Originality/valueAnalysis of SCFs in regard to performance measures during SPS helps improve supply chain performance and offer valuable insights to the practicing managers in decision-making. This study augments the flexibility literature, by clubbing the two independent research streams, SCF and SPS.

A Flexible Policy Framework for Analysing Multimodal Freight Transportation System in India: SAP–LAP and Efficient IRP Method

Freight logistics sustainability is a prime concern of supply chain actors and policymakers. Many of the countries promoted a multimodal freight transportation system for enhancing transport sustainability. The development and promotion of multimodal services in developing nations are lacking and face many sustainability challenges. These challenges are linked to the CO2 emission, traffic congestion, longer travel time, poor transport infrastructure, and transport mode inequality. To address these challenges, this paper is to analyse the multimodal freight transport practices in India and propose adequate policy measures to uplift the freight modal imbalance and transport sustainability. In this paper, situation–actor–process (SAP) and learning, action, performance (LAP) framework is used to analyse the research problem. Further, the interrelationship among the various elements of SAP–LAP is analysed thorough cross-interaction matrices and their dominance profile. The efficient interpretive ranking process is used for prioritization of the actors with respect to processes and actions with respect to performance. The research findings show that Government policymakers and Indian railways are the most influential actor for improving the share of multimodal services. Likewise, the operationalization of a dedicated freight corridor and the use of multimodal services for long hauling are top actions recommended for improving the sustainability performance of freight transportation. The dominance profile of actors and actions is presented. This paper also elucidates the managerial implications of the research.