Analysis of barriers of cyber-physical system adoption in small and medium enterprises using interpretive ranking process

PurposeThe 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).Design/methodology/approachIn 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.FindingsThe 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.Research limitations/implicationsIn the present study, barriers for CPS adoption has been analyzed. In future, barriers for adopting other Industry 4.0 technologies could be analyzed.Practical implicationsThe 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.Originality/valueThe analysis of barriers for CPS adoption in SMEs is the original contribution of the authors.

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.

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.

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.

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.

Modelling of risk factors for defence aircraft industry using interpretive structural modelling, interpretive ranking process and system dynamics

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value The outcomes of this research can help project management team to identify the high severity risk factors which need immediate risk reduction/mitigation action.

Using integrated weighted IRP-Fuzzy TISM approach towards evaluation of initiatives to harmonise Halal standards

PurposeMultiplicity and conflicting Halal standards involve unnecessary repetition of testing for demonstrating the Halal integrity of the process and the product, thus making it difficult for the Halal commodities to get traction in international markets. The purpose of this paper is to suggest initiatives to facilitate harmonisation of Halal standards as to eliminate trade barrier of Halal and to assure the availability of Halal consumables to larger masses.Design/methodology/approachRanking of the initiatives for the harmonisation of Halal standards taking in consideration the costs of accomplishment and associated benefits obtained has been done through the application of integrated Interpretive Ranking Process (IRP) and Fuzzy Total Interpretive Structural Modelling (Fuzzy TISM). This integrated methodology with the weighted criteria have refined the value of the net dominance of different variables, thereby increasing the efficacy of IRP in decision making.FindingsFindings suggest that strengthening the strategic coordination and collaboration among competent HCBs is a significant initiative. This initiative needs to be undertaken to mitigate the conflict between HCBs. This necessitates to develop a common platform in making the collective decision for effectively controlling Halal businesses. Moreover, recognising competent HCBs will prompt the effective implementation and execution of Halal standards across the supply chain, and ease the global trading of Halal products. A framework has been conceptualised to enable harmonisation of Halal standards which intimates to develop globally agreed protocols for Halal practices.Practical implicationsThe framework presented may act as a prelude to harmonise Halal standards and may positively affect the international trade of Halal commodities by phasing out the discriminatory and market-impeding standards.Originality/valueA harmonised system may provide correct information to the stakeholders and may help in making an informed decision.

Interpretive framework for analyzing lean implementation using ISM and IRP modeling

Purpose 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. Design/methodology/approach 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. Findings The proposed framework can help firms better understand LPs and their levels of importance in lean implementation. Research limitations/implications The involvement of lean experts may produce some bias in evaluating the LPs. Practical implications 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. Originality/value 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.