Search results

Agile new product development (ANPD) attracts researchers and practitioners by its ability to rapidly reconfigure products and related processes to meet the needs of emerging markets. To increase ANPD adoption, this study aims to identify ANPD enablers (ANPDEs) and create a structural framework that practitioners can use as a quick reference.

Initially, a comprehensive literature review is conducted to identify ANPDEs, and a structural framework is developed in consultation with an expert panel using a hybrid robust best–worst method interpretive structural modeling (ISM). During the ISM process, the interactions between the ANPDEs are investigated. The ISM result is used as input for fuzzy Matrice d’Impacts croises-multiplication appliqúean classment means cross-impact matrix multiplication applied to classification (MICMAC) analysis to investigate enablers that are both strong drivers and highly dependent.

The study’s findings show that four ANPDEs are in the low-intensity cluster and thus are excluded during the structural frame development. ISM output shows that “Strong commitment to NPD/top management support,” “Availability of resources,” “Supplier commitment/capability” and “Systematic project planning” are the important ANPDEs. Based on their driving and dependence power, the clusters formed during the fuzzy MICMAC approach show that 16 ANPDEs appear in the dependent zone, one ANPDE in the linkage zone and 14 ANPDEs in the driving zone.

This research has intense functional consequences for researchers and practitioners within the industry. Industry professionals require a conservative focus on the established ANPDEs during ANPD adoption. Management has to carefully prepare a course of action to avoid any flop during ANPD adoption.

The framework established is a one-of-a-kind study that provides an integrated impression of important ANPDEs. The authors hope that the suggested structural framework will serve as a blueprint for scholars working in the ANPD domain and will aid in its adoption.

This paper aims to identify the interrelationships among critical factors for digital servitization (DS) implementation.

A multi-method research was used. Critical factors for a successful DS implementation were identified using a systematic literature review and expert interviews. The interpretive structural modeling (ISM) method was used to develop a hierarchical model of the identified factors, followed by the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis to assess their dependence and driving powers.

A total of 23 factors for DS implementation were identified, and the ISM model was developed. Based on MICMAC analysis, the factors were also grouped under four categories (dependent, driving, autonomous and linkage). A conceptual framework is proposed, highlighting that DS implementation relies on three main layers of critical factors: crafting alignment, scaling the change and achieving results.

The ISM and fuzzy MICMAC methods used in this study provided valuable insights into the interrelationship among the identified DS factors through a conceptual framework. To the best of the authors’ knowledge, the study is one of the first to identify critical factors influencing DS implementation and develop hierarchical relationships among them.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

Various publications have extensively documented the advantages of a circular economy in ensuring sustainability and limiting climate change. Despite academic records emphasising the need to adopt this business strategy, entrepreneurs in developing countries prefer linear economies. This reluctance is attributable to several factors, including insufficient infrastructure and technology, limited financial access, inadequate education systems and the prevalence of informal enterprises. Therefore, a thorough analysis of the underlying economic, political and social conditions is required to identify the drivers of circular economies (CEs) and their contribution to entrepreneurship in developing countries.

In this study, the authors first conducted a comprehensive quantitative literature review based on LangChain to identify the critical CE drivers from the social, technological and organisational perspectives. Based on the input from the expert panel of Iranian academic and industry professionals, the authors applied an integrated fuzzy interpretive structural modelling and cross-impact matrix multiplication approach to classification (Fuzzy-ISM-MICMAC) to investigate the chronology of entrepreneurial drivers.

Level-based model results reveal entrepreneurial drivers in developing nations and their interrelationships, specifically underlining the importance of supply chain factors and stakeholder preferences. Thus, the differences between the perception of the main drivers in developed and developing economies can be identified, with the former paying particular attention to legislative and financial factors. The study's findings contribute to conserving resources, reducing waste and adopting more sustainable corporate practices, thereby assisting developing countries in achieving development goals.

This study employs an innovative quantitative systematic literature review approach that relies on a large language model to identify the drivers of the CE. Furthermore, it adopts a systematic approach to examine the enablers of the CE rather than a narrow and individual perspective of the entrepreneurial drivers. The study employs the fuzzy ISM MICMAC technique to showcase the prioritisation of entrepreneurial prospects in emerging economies.

Building information modeling (BIM) is a popular technology in modern construction, but its implementation faces numerous difficulties, which are known as problematic issues of BIM implementation (PIBIs). This study aims to identify and analyze PIBIs based on the perceptions of practitioners in Vietnamese BIM-implemented construction contractors and similar BIM adoption-level countries.

The research is conducted in three stages. After a comprehensive literature review, PIBIs are identified and ranked based on the Delphi method and questionnaire survey. Next, interpretive structural modeling (ISM) is used to provide a hierarchy of system PIBIs. Finally, the driving and dependence power of PIBIs are determined using Fuzzy-Matrice d'Impacts Croisés-Multiplication Appliquée à un Classement (MICMAC) analysis.

This study evaluates 32 PIBIs for small and medium contractors (SMCs) and 28 PIBIs for large contractors (LCs) in Vietnam. This study also develops a systematic framework for contextual relationships and analyzes the relationships among PIBIs using ISM-Fuzzy MICMAC analysis. The results show that different standards or techniques, modeling software limitations and information management significantly impacted LCs, while a lack of senior leadership support and incompatible software affected SMCs, causing other PIBIs.

This study is among the first attempts to investigate the problematic issues emerging during the BIM implementation process at the organizational level in Vietnam as well as other developing countries. The study results could be considered valuable references for BIM practitioners. Furthermore, this knowledge can enable contractors to avoid problems while adopting BIM, thereby increasing their ability to implement BIM successfully and using critical resources more efficiently.

Small and medium enterprises (SMEs) significantly contribute to economic growth, development, exports and employment of the nations. To maintain competitiveness in today's market, SMEs must explore and identify enablers to enhance their digital transformation process. This paper aims to shed light on some essential enablers SMEs can use to implement digital resilience successfully.

The quantitative assessment and validation of the enablers have been done using powerful and novel techniques, namely, the Delphi method, “fuzzy interpretive structural modelling” (F-ISM) method and “cross-impact matrix multiplication applied to classification (MICMAC)” analysis. The F-ISM model is developed using the information drawn from digital transformation experts and practitioners involved in the digital transformation process for SMEs. Furthermore, the F-ISM model provides four paths to complete the pathway to digital resilience.

The F-ISM and MICMAC analysis revealed four ways to enhance the digital transformation process in SMEs. These enterprises can utilise these path assessments to become digitally resilient in the present dynamic scenario. To enhance digital resilience among SMEs, the study identified ten enablers. Among these, “management competencies” was the most crucial, followed by “knowledge management” and “monitoring and controlling”.

The present study is limited in that the data used to develop the models were collected from a small group of industry experts whose opinions may not exhibit the comprehensive views of the population.

The findings can help SMEs enhance the digital transformation process by taking up different pathways to integrate the various enablers of digital resilience depending on resource availability.

The results indicate the most critical and influential enablers for enhancing digital resilience among SMEs. This research can be valuable to academicians, industry practitioners and researchers for guiding their future work.

The concept of productive entrepreneurship has been recognised as a strategic approach to address the various challenges economies face, such as high unemployment, low economic growth and limited diversification. However, studies on the productive entrepreneurship’s critical success factors (CSFs) are rare and fragmented. Hence, this paper aims to identify the CSFs of productive entrepreneurship and determine their relationship among to offer a meaningful framework for enhancing the result of entrepreneurial activities in the emerging economy.

The authors conducted an extensive literature review and consulted experts to identify 14 CSFs for productive entrepreneurship. The technique of interpretive structural modelling (ISM) was used to determine the relationships and interconnectedness between these factors. In addition, this study used matrix of cross-impacts applied to a classification (MICMAC) analysis to determine the significance of CSFs in relation to the productive entrepreneurship.

The results indicate that the regulatory environment, incubators and accelerators and mentorship were the most influential factors for productive entrepreneurship in the Indian context. In contrast, social mobility and resilience were found to be the least influential factor.

The study's findings can enable researchers, policymakers and entrepreneurs to make informed decisions and develop effective strategies to enhance the productive entrepreneurship.

The unique approach of research (ISM and MICMAC analysis) expands the frameworks of the entrepreneurship ecosystem with a comprehensive and dynamic emergent investigation into the foundation of productive entrepreneurship.

The apparel and textile sector poses a significant environmental challenge due to its substantial contribution to pollution in the form of air, water and soil pollution. To combat these issues, the adoption of sustainable practices is essential. This study aims to identify and analyse the barriers that hinder the progress of sustainability in the apparel and textile industry. By consulting experts in the field, critical barriers were identified and given special attention.

To achieve the research objective, an integrated approach involving Interpretive Structural Modelling (ISM) and fuzzy MICMAC decision-making techniques was employed. The results were further validated through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The findings highlight that barrier related to clothing disposal, inadequate adaptation to modern technology, challenges affecting sector efficiency and issues related to fashion design are crucial in influencing the remaining six barriers. Based on the outcomes of the DEMATEL method, a comprehensive cause-and-effect diagram was constructed to gain a deeper understanding of these challenges.

This research provides valuable insights for policymakers and stakeholders in the apparel and textile industry. It offers a strategic framework to address and overcome sustainability barriers, promoting the development of a more environmentally responsible and resilient sector.

The purpose of this research is to conduct an in-depth investigation of the barriers apparel and textile sectors. It is feasible that both the management team and the medical experts who provide direct patient care could benefit from this research.

The objectives of this study are as follows: RO1: to determine the key enablers that encourage the adoption of sustainable practices; RO2: to create a structural relationship model between the enablers that have been discovered and RO3: to use dependence and driving power to classify and analyse these factors.

In total, 11 variables were extracted through systematic literature review and experts opinion, and a group interview with more than 15 experts who have an experience of more than 10 years in academics was conducted. Generally odd in numbers, they presented each pair of variables and took their opinion. Using “Interpretative Structural Modelling” and “Cross-Impact Multiplication Applied to Classification” (ISM MICMAC) analysis, a model describing the structural relationship between these factors has been formulated to know the conceptual framework.

The study shows that the digital payment and waste treatment as the linkage or mediating variables. Top management commitment (TMC), regulatory framework and transparency are the drivers or independent variables. Green logistics, sustainable packaging and production are the dependent variables. Further, the resulting hierarchy and contextual linkages among variables shed light on key dimensions for decision-making. Green logistics, sustainable packaging and production are interconnected, playing a significant role, in the framework and influenced by the lower level variables. Transparency should be given due consideration to ensure sustainable competitive advantage.

(1) Owing to a lack of time and resources, the researchers have been able to explore only limited variables; more factors or enablers can be taken in future for further research. (2) Money constraint is also there. (3) One major limitation is that this research includes opinion from different experts which are dynamic in nature and keep on changing from time to time. (4) Primary research can also be done with the help of different software like partial least squares and structural equation modelling (PLS-SEM), covariance-based structural equation modelling (CB-SEM) and Statistical Package for the Social Sciences (SPSS) by taking same variables or merging new variables with the given variables of this paper. (5) With the help of this paper, the author tried to give an overview of some important enablers which are helpful in sustainability. Given a time in future, more research can be done by taking different sectors or a specific sector.

Findings are helpful for policymakers about effective strategies for promoting sustainability. They provide evidence-based insights into the potential impact of policy interventions and help shape the development of environmental regulations and initiatives. Sustainability is a global issue. Thus, this research paper contributes to international discussions and collaborations on environmental conservation and sustainable development goals (SDGs). They may influence diplomatic efforts to address transnational environmental challenges. Companies can use research findings to improve their sustainability practices and develop environmentally friendly products and services. Understanding sustainability enablers can help businesses reduce their ecological footprint while remaining economically viable. Research on sustainability enablers often involves exploring new technologies and innovations. Practical implications include the development and adoption of renewable energy sources, waste reduction techniques and sustainable agricultural practices. Sustainable communities rely on a range of enablers, from renewable energy infrastructure to local governance structures. Research informs community development efforts by identifying best practices and effective strategies for building resilient, environmentally friendly neighbourhood.

This research paper contributes to raising awareness about sustainability issues among the public. It also provides insights into the importance of sustainable practices and their impacts on society. Sustainability enablers can influence individual and collective behaviour, and they may encourage people to adopt more sustainable lifestyles and consumption habits. Sustainability research often addresses issues of equity and social justice. Understanding the enablers of sustainability can help identify strategies to ensure that sustainable practices benefit all segments of society, including marginalized communities.

This research paper endeavour to identify key sustainability development enablers (SDEs) by consolidating numerous factors within a single study. While several research papers have explored various sustainability enablers separately, no previous study has delved into their interactions. Furthermore, there is a dearth of research on classifying enablers based on the fuzzy MICMAC analysis. The ISM-based model presented here serves as a valuable resource for both practitioners and academics, aiding in their comprehension of the framework of relationships.

The disruptive pandemic has badly affected supply chain operations across the globe and implementing green supply chain strategies is challenging for manufacturing firms, especially in emerging countries. Therefore, this study aims to identify the significant challenges hindering the green supply chain as a pathway towards sustainability in the post-COVID-19 era.

Fuzzy Delphi Methodology (FDM), Interpretive structural modeling (ISM) and MICMAC were applied. FDM was applied to select the most relevant challenges and later ISM and Matrices d'Impacts cross-multiplication appliqúe a classmate MICMAC were used for modeling and classifying critical challenges.

Lack of trust between firms and supply chain partners, and difficulty in transforming positive environmental attitudes into action are the significant challenges to implementing green supply chain management. Lack of communication between government and Chinese firms is the least important factor which shows that the government is trying to support firms and reduce the negative effects after the drastic impacts of COVID-19. However, COVID-19 left a draconian effect on organization’s green supply chain and it’s not easy to overcome.

None of the previous studies applied mixed methodologies of FDM, ISM and MICMAC to evaluate Green supply chain as a pathway to sustainable operations in the post-COVID-19 era. Challenging factors of green supply chain operations in COVID-19 are different from earlier studies and contribute to the literature of emerging countries.