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The paper introduces a discussion regarding the development of a public bike-sharing system, considering random factors, based on selected external environmental analysis methods. The global energy crisis is forcing scientists to continuously improve energy-efficient sustainable methods and scientific solutions. It is particularly important in transportation since transport activities and the constant increase in the number of vehicles have a large share in global energy consumption. The following study investigates the social, technological, economic, environmental, and political aspects of bike-sharing systems in cities. The research purpose of the article is to select the most important macro-environmental factors and their mutual interaction influencing the sustainable development of bike-sharing systems based on the Polish cities case study. The evaluation was carried out through expert methods with STEEP environmental analysis, evaluation of factors with the weighted score, and structural analysis method with MICMAC computer application. The classification of key factors influencing the development of a bike-sharing system has divided them into five groups. It can support public transport service providers and organizers. This can optimize the planning process with decision-making based on future environmental trends.

PurposeThe vision of Industry 4.0 concept is to create smart factories that will change the current processes of production and manufacturing system using smart machines to produce smart and intelligent products. The main aim of this research is to explore the enablers with regard to Industry 4.0 application in manufacturing industry in India as the available literature shows that manufacturing sector is still doubtful about the implementation of Industry 4.0.Design/methodology/approachSeventeen enablers that can affect the adoption of Industry 4.0 in the manufacturing industry in India have been explored through an extensive review of available literature and viewpoints of industry and academic experts. Total Interpretive Structural Modelling methodology (TISM) has been used to evaluate the interrelationships among these factors. A TISM model has been developed to extract the key enablers influencing Industry 4.0 adoption.FindingsThe result shows that Internet facility from government at reduced price, financial support and continued specialized skills training are the major enablers as they have strong driving power.Practical implicationsProper understanding of these enablers will help the managers and policymakers to explore the impact of each enabler on other enablers as well as the degree of relationships among them and to take concrete steps so that Industry 4.0 can be implemented successfully in the manufacturing sector in India.Originality/valueThis study is pioneer in exploring the enablers Industry 4.0 which is the most advanced concept that has the capability to change the future of Indian manufacturing sector if implemented judiciously and cautiously.

Technologies are developing at a fast rate in which every new technology has an ample range of applications. Digitalization has taken rapid strides over the last few years which plays an important role in Industry 4.0. The digital revolution is fundamentally changing the way people live and work, and the public is optimistic about the opportunities Industry 4.0 can offer for sustainability. All organizations or industries have not been equipped with the latest technologies to adopt digitalization. This is mainly due to the lack of knowledge and expertise and unclear benefits of the technology. The study identifies the potential barriers in the adoption of digital technologies through two processes namely Total Interpretive Structural Modelling (TISM) and Matrix Multiplication Applied to Classification (MICMAC) analysis. Using these models, the study interprets the barriers and analyses the relationship between the barriers. The barriers need to be treated on a priority basis and must be eliminated to successfully adopt digital technologies. From the developed TISM model and MICMAC analysis, the most influential barrier for the adoption of digital technologies in Industry 4.0 are negative perception towards technology because, this barrier will not depend on other barriers and hence managers must give a topmost priority to avoid the disruption in the system for the adoption of digital technologies. The study talks about other key barriers which influence the implementation of Industry 4.0, some of them being unclear benefits and lack of awareness. These barriers act as the primary variables which disturb the system and hinder the approach while additional barriers pose as secondary variables in the system. This research aims to help Industry 4.0 stakeholders – public and private sector leaders, industrialists– to get a lot more clarity on the opportunities that the digital revolution can offer for sustainability and to ensure that Industry 4.0 delivers sustainable functions.

The purpose of this paper is to explore the enablers for the implementation of electronic traceability in agri-food supply chain in India. In several agri-food supply chains, the lack of any form of traceability or the presence of paper-based traceability impacts the trade of the concerned food product. Electronic traceability (e-traceability) will assist agri-food firms in improving their performance, minimize food fraud activities, ensure efficient recall of the products and contribute in overall agri-food supply chain management. With the help of literature review and expert opinions, enablers of e-traceability are modelled and analyzed using Fuzzy ISM and FUZZY MICMAC. The combination of both these techniques helps in identifying the essential drivers in the implementation of e-traceability in agri-food supply chains. The proposed approach found that that electronic form of traceability is better than paper-based traceability in agri-food supply chains. The significant drivers in e-traceability implementation, particularly in agri-food supply chain are appropriate technology for e-traceability, competitive advantage, coordination and transparency and management support. The identified enablers would guide the managers or decision-makers in the adoption of e-traceability in their existing supply chains in the agri-food sector.

Sustainable supply chain (SSC) practices are identified as the key solutions to deal with the rise in environmental issues, institutional pressures related to the environment, and pollution. Literature highlights that Industry 4.0 technologies enable the implementation of SSC practices and have the great potential to achieve sustainable performance by minimizing the use of resources and energy. Scholars have acknowledged the need to understand how Industry 4.0 technologies enabled SSC practices lead to gain sustained competitive advantage and sustainable performance. This research study investigates the recent trends in the literature on Industry 4.0 and SSC management areas by using a systematic literature review (SLR) and bibliometric analysis. Based on the findings of the SLR and inputs from the experts (both from academia and industry) associated with Indian manufacturing industries, an indicative list of critical success factors (CSFs) has been identified. The interrelationships between these CSFs have been analyzed using interpretive structural modeling (ISM) and MICMAC analysis. Further, using the insights gained from the SLR and ISM–MICMAC analysis and combining them with the relevant existing organizational theories namely institutional pressure (IP) theory, resource-based view (RBV), and dynamic capabilities view (DCV), this study puts forward a theoretical model and six propositions. The analysis shows that “Governmental support and policies”, “Futuristic goals, vision”, “Top management support, commitment, and leadership”, and “Competition”, are some of the important CSFs to adopt SSC practices in the Industry 4.0 era. Further, it is observed that a “Skilled workforce”, “Knowledge management”, and “Technological capabilities” aid in the generation of innovative competencies such as the better implementation of SSC practices integrated with Industry 4.0 technologies, better supply chain integration, waste reduction, etc. These high-order innovative capabilities help organizations to achieve higher profitability, higher sustainable performance, and continuous competitive advantage in the dynamic business environment.

PurposeThe main objective of this paper is to justify the implementation of blockchain (BC) over the traditional method deployed in the supply chain (SC) after using the fuzzy–analytic network process (fuzzy-ANP) application. Over the past two decades, the overall product cost is affected by the SC at a global level. Organizations are working on their existing SC for improving their performance. BC technology is a newly emerging technology and magnetizes the attention of researchers and industrialists. This technology is still at the initial stage, and only little investigation is available in the literature and it has not been much investigated by researchers.Design/methodology/approachLiterature and expert opinion interpretation in BC characteristics are further analyzed and modeled using fuzzy–interpretive structural modeling (fuzzy-ISM), fuzzy-MICMAC and fuzzy-ANP. The combined approach of both fuzzy-ISM and fuzzy-MICMAC is applied to identify the common drivers to integrate the BC technology in the light of efficient supply chain management (SCM).FindingsComparative analysis between traditional and BC-based supply chain (BCSC) using fuzzy-ANP is carried out, considering the common driving characteristics. The proposed integrated (combined) approach of fuzzy-ISM, fuzzy-MICMAC and Fuzzy-ANP found that integration of BC with SCM is better prioritized than traditional supply chain management (TSCM). The findings in the article endorse that the TSCM can be made efficient by integrating the BC technology considering five most driving characteristics, namely, data safety and decentralization, accessibility, documentation, data management and quality.Originality/valueThe current proposed research work identifies 12 characteristics after studying numerous literature reviews and having a discussion with SC experts with knowledge of BC. The integrated approach of fuzzy-ISM and fuzzy-MICMAC is implemented here. After that, fuzzy-ANP is used to give ranking among BCSCM and TSCM. The study carried out in this article motivates industries to implement BC in their SC system. It will reduce the transaction cost, documentation work, save time and eliminate human error at the national and international levels. The common characteristics identified in this proposed work would help in managerial decisions for the adoption of BC to ensure that the system becomes more transparent, easily traceable and finally improve the performance.

Interpretive Structural Modeling (ISM) is a technique to establish the interrelationships between elements of interest in a specific domain through experts’ knowledge of the context of the elements. This technique has been applied in numerous domains and the list continues to grow due to its simplistic concept, while sustainability has taken the lead. The partially automated or manual application of this technique has been prone to errors as witnessed in the literature due to a series of mathematical steps of higher-order computing complexity. Therefore, this work proposes to develop an end-to-end graphical software, SmartISM, to implement ISM technique and MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (cross-impact matrix multiplication applied to classification)), generally applied along with ISM to classify variables. Further, a scoping review has been conducted to study the applications of ISM in the previous studies using Denyer and Tranfield’s (2009) framework and newly developed SmartISM. For the development of SmartISM, Microsoft Excel software has been used, and relevant algorithms and VBA (Visual Basic for Applications) functions have been illustrated. For the transitivity calculation the Warshall algorithm has been used and a new algorithm reduced conical matrix has been introduced to remove edges while retaining the reachability of variables and structure of digraph in the final model. The scoping review results demonstrate 21 different domains such as sustainability, supply chain and logistics, information technology, energy, human resource, marketing, and operations among others; numerous types of constructs such as enablers, barriers, critical success factors, strategies, practices, among others, and their numbers varied from 5 to 32; number of decision makers ranged between 2 to 120 with a median value of 11, and belong to academia, industry, and/or government; and usage of multiple techniques of discourse and survey for decision making and data collection. Furthermore, the SmartISM reproduced results show that only 29 out of 77 studies selected have a correct application of ISM after discounting the generalized transitivity incorporation. The outcome of this work will help in more informed applications of this technique in newer domains and utilization of SmartISM to efficiently model the interrelationships among variables.

The Pakistan construction industry recorded a high growth rate of 9.05% in 2016–2017. However, it fails to complete the projects within the specified cost, time and quality due to the use of traditional management techniques. This can be easily overcome by adopting and implementing new technologies like Building Information Modeling (BIM). In this study, a questionnaire survey was performed to find the present state of BIM in Pakistan and highlight the barriers in its successful adoption. In addition, Interpretive Structure Modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis were used to identify interrelationships among these barriers. Out of 104 responses received, 63% of Architecture, Engineering and Construction (AEC) professionals were aware of BIM and among them, only 17% had utilized BIM in their projects, which is a very low percentage. The adoption of BIM in Pakistan is only at 11%. The respondents acknowledged that BIM helps in minimizing the cost and time of a project up to 57%. This study concluded that BIM is more economical and efficient than other management techniques. Moreover, this research also identifies the ISM and MICMAC analysis-based hierarchical model and three level strategy model that can facilitate the possible implementation. Solutions to common barriers around the globe are also proposed. Thus, by utilizing BIM, an economical, timely, properly managed project can be obtained in Pakistan and other developing construction markets all over the globe.

PurposeBlockchain technology (BCT) can be used for a wide variety of applications across domains and can bring many benefits. BCT-based applications can be beneficial for the government as well as businesses. Despite the many promises, BCT implementation lags behind. The purpose of this research is to identify a roadmap of critical implementation challenges that influence BCT implementation by governments.Design/methodology/approachThe study develops an ISM-based model spread across seven levels to analyze the inter-relationship among the selected BCT challenges. The MICMAC analysis further helps in evaluating the variables based on their driving power and dependencies.FindingsThe findings show that all challenges have a strong impact on implementing BCT. The foundation for implementation BCT is to define standards and develop appropriate regulations. Next, the findings show the need for a shared infrastructure meeting the basic technical and societal requirements and developing viable business models to advance BCT implementation. Many challenges hinder the development of blockchain applications meeting the technical and ethical requirements.Originality/valueExisting research has analyzed the relationship among challenges. To the best of the authors' knowledge this is the first paper to collate these implementation challenges and incorporate them to develop a hierarchical model using interpretive structural modeling technique. The results can be used to prioritize the tackling of the challenges.

PurposeBig data analytics (BDA) is recognized as a recent breakthrough technology with potential business impact, however, the roadmap for its successful implementation and the path to exploiting its essential value remains unclear. This study aims to provide a deeper understanding of the enablers facilitating BDA implementation in the banking and financial service sector from the perspective of interdependencies and interrelations.Design/methodology/approachWe use an integrated approach that incorporates Delphi study, interpretive structural modelling (ISM) and fuzzy MICMAC methodology to identify the interactions among enablers that determine the success of BDA implementation. Our integrated approach utilizes experts' domain knowledge and gains a novel insight into the underlying causal relations associated with enablers, linguistic evaluation of the mutual impacts among variables and incorporating two innovative ways for visualizing the results.FindingsOur findings highlight the key role of enabling factors, including technical and skilled workforce, financial support, infrastructure readiness and selecting appropriate big data technologies, that have significant driving impacts on other enablers in a hierarchical model. The results provide reliable, robust and easy to understand insights about the dynamics of BDA implementation in banking and financial service as a whole system while demonstrating potential influences of all interconnected influential factors.Originality/valueThis study explores the key enablers leading to successful BDA implementation in the banking and financial service sector. More importantly, it reveals the interrelationships of factors by calculating driving and dependence degrees. This exploration provides managers with a clear strategic path towards effective BDA implementation.