Analysing influencing factors and correlation paths of learning burnout among secondary vocational students in the context of social media: An integrated ISM-MICMAC approach

By analysing the factors influencing secondary vocational students' learning burnout in the context of social media, this study unearthed the underlying causes of learning burnout. It also determined the correlation paths among the factors influencing learning burnout, providing references for educational and pedagogical improvement. This contributes to preventing secondary vocational students' learning burnout and enhancing learning efficiency in secondary vocational schools. Combined with previous research results and a theoretical basis, this study identifies 10 influencing factors employing the Delphi method, and uses Interpretative Structural Modelling (ISM) and Matrice d' Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) to elucidate the relationship between influencing factors of learning burnout among secondary vocational students in the context of social media. This study also constructs a corresponding mechanism model and subsequently proposes prevention and improvement strategies. The results show that the overdevelopment of social media, as driving factors, has the greatest impact on secondary vocational students' learning burnout. Simultaneously, it takes the lead in addressing cognitive bias among students, decreased self-control, and low learning efficiency, factors that contribute to learning burnout. This is particularly beneficial in alleviating the degree of learning burnout among secondary vocational students in the context of social media and improves overall learning outcomes for these students. The hierarchical structure and correlation paths identified in this study offer robust invaluable guidance for developing a scientific program to address the problem of learning burnout among this demographic. This includes implementing related educational practises, thereby reducing the unpredictability of the practical applications.

Understanding green procurement dynamics: An assessment framework for public sector organizations

Governments globally face increasing pressure from climate advocates and international agreements, such as the Paris Agreement, to enact policies addressing climate change. This paper addresses the imperative for sustainable practices outlined in such agreements, with a specific focus on assessing the drivers of Green Procurement Practices (GPP) within Public Sector Organizations (PSOs). A dearth of research exists in systematically analyzing and prioritizing these drivers, exploring their interdependencies, and elucidating their relative importance. GPP is pivotal in market transformation by promoting environmentally friendly products and endorsing low-carbon, energy-efficient alternatives. This, in turn, contributes significantly to mitigating climate change and fostering a shift towards a greener, more sustainable economy. Identification of the drivers has been performed by an extensive review of the literature combined with the author's viewpoint, while the analysis has been performed using the novel method of Dominance-based Rough Set Approach (DRSA) and Interpretive Structural Modelling (ISM) with Matriced' Impacts Croise's Multiplication Applique'e a UN Classement (MICMAC) analysis. The study's outcome reveals that the Demand for Eco-friendly products is the primary driver for the incorporation of GPP, followed by the drivers' Presence of guidelines support and Government Regulations. Findings of the research also demonstrate that suppliers' propensity to adopt green practices depends on several factors, including sustainable supplier cooperation, degree of commitment to embrace green initiatives, government interventions in the form of incentives and guidelines support, and the presence of a legal framework. The findings of this research will enrich the understanding of policymakers and managers to formulate strategies for advancing GPP structured and sustainable implementation in PSOs. The study's findings will also benefit green technology sector advancement through the widespread adoption of GPP.

Construction land reduction projects as a pathway to sustainability: an empirical analysis of risks factors in China

Construction land reduction (CLR) is an effective instrument to improve intensive land use, restrict the expansion of construction land, safeguard the requisition-compensation balance of construction land in China, and realize sustainable development. But multiple risks arise from the process of construction land reduction. In that case, identifying and analyzing the key risks of CLR is the prerequisite for formulating practical policy guidelines. This study is conducted to identify the risk factors of CLR and analyze these risks based on expert opinion. Initially, the original risk factors are sourced from existing literature. In order to tailor them to China's specific context, the Delphi method is employed to systematically refine risk definitions, consolidate similar risk elements, and identify any previously unrecognized risks in the literature. Following an in-depth review of the literature, we create a contextual relationship-based model employing an integrated technique of interpretive structural modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. Based on the ISM and MICMAC analysis, five key risks were identified, and the prevention strategies and policy recommendations for CLR project risks are put forward.

Barriers to Minimisation of agri-products wastage through Optimizing logistics in India: An ISM modelling approach

The research work identifies and priorities the factors affecting agri-logistics causing wastage of the agricultural products during its transit from farm to the point of consumption so that logistics mechanism for agriculture sector in India can be optimised by removing the barriers leading to hindrances in safe, timely, economical and good condition delivery of the agri consignment. The field of agri-logistics remains at the crucial nexus of the agricultural and logistics industries and has the potential to improve the nation's system for distributing food. The post-harvest wastage in India has been massive due to inefficiencies agri-logistics management and faulty food distribution mechanism. It is an exploratory study that along the factors (barriers) identified and synthesised from literature review of the concerned area. The identified barriers were reduced and finalised in consultation with the experts using Delphi technique. With the help of ISM questionnaire, a model has been developed reflecting the drivers and dependents out of the barriers considered for the study. The result is further validated through MICMAC analysis. The result of the study has come up with the interpretive structure model depicting hierarchy of the barriers pushing from down to top causing agriculture wastage. The paper holds originality in the sense that it comes up with fresh perspectives on the factors causing hindrances in the efficient logistics operation that certainly helps to minimise wastage of the agri-products in the post-harvest stages. The identification of the barriers and their detriments to the other factors will help to take essential steps on how to overcome the issues and optimize the agri-logistics that would minimise the agri-wastage in India and prove to be a game changer to the agri-trade sector.

Evaluating the social outcomes of COVID-19 pandemic: empirical evidence from Pakistan

The study aims to assess and analyze the social outcomes of the COVID-19 pandemic. The study uses the discourse of comprehensive literature review to identify the outcomes, Interpretive Structural Modeling (ISM) for developing a structural model and Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) for analysis, classification of societal outcomes, and corroboration of results of ISM. Data from fifteen experts was collected through a survey questionnaire. As a result of the literature review, a list of sixteen outcomes was generated and verified by a panel of experts. Results of ISM revealed that the outcomes, namely, "emotional instability," "mental health self-harm," loneliness reduced recreational activities, obesity, and "increased screen time" come at the top of the model; therefore, they are less vital outcomes, whereas the most significant outcome which is at the bottom of the model is "employment instability"; hence it has a major impact on the society. The remaining outcomes fall in the middle of the model, so they have a moderate-severe impact. Results of MICMAC validate the findings of ISM. Overall findings of the study reveal that "employment instability" is the crucial social outcome of the COVID-19 pandemic. It is an original attempt based on real-time data, which is helpful for society at large, researchers, the international community, and policymakers because this study provides a lot of new information about the phenomenon. The study includes understanding society at large, policymakers, and researchers by illustrating the complex relations and simplifying the connections among a wide range of social outcomes of COVID-19.

Assessment of sustainable green financial environment: the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic

The study aims to assess a sustainable green financial environment by exploring the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic. This study is qualitative and uses a review of literature, primary data collection methods, and qualitative analysis techniques as the study's overall design. The data is collected by one-to-one interview using a matrix style questionnaire from a panel of experts based on the purposive sampling technique. Interpretive structural modeling (ISM) combined with Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used for assessment, modeling, and analysis of data. The monetary aftershocks, namely, "more cash in hand required," "decreased travel costs," "shift to more certain or fixed revenue streams," "lower rent costs," "more zealous monitoring of cash collection cycle," and "decreased entertainment costs," occupy level I (top of the model being least critical shocks), and "tedious regulations" occupy level VIII (bottom of the model being the most vital). Other aftershocks form the middle of the model being moderate critical. Analysis of MICMAC shows that monetary seismic aftershocks high fees for assistance regarding SOPs, tedious regulations, and more downtime due to pandemic alerts are independent. This study addresses the core issue from within the aftermath of the COVID-19 pandemic. It provides new important information regarding the structure of a sustainable green financial environment that is useful for economists, financial analysts, commercial and central bankers, accountants and finance managers from the organization's public/and private sectors, local and international community, and researchers of the domain. It provides an informative structural model and classification of critical aftershocks. There are specific data/methodological/resource-related limitations of the study. The study's data are collected from a focus group; the study's methodology is qualitative and indicates relations among variables that do not quantify the associations. The study is a typical initiative of academic researchers with limited financial/physical resources; therefore, the generalizability of the study results is accordingly limited. The study is based on original, essential data and innovatively and creatively approaches the problem. It provides a unique model of an unprecedented phenomenon for reverberating the sustainable green financial environment.

Establishing a Green, Lean and Six Sigma implementation model for sustainable construction industry: an analysis of driving forces through ISM-MICMAC approach

Green Lean Six Sigma adoption (GLSA) is an emerging concept that enhances product quality, safety and the overall performance of the firms. Few studies attempted to explore and examine the DFs of GLSA towards creating a strong urge in the stakeholders for long-term economic, ecological and productivity advantages. Major 32 DFs were initially explored to fill this gap by conducting a literature review and semi-structured interviews with different experts. Then, using the Delphi method, 28 DFs pertinent to the construction industry of Pakistan were screened, and established a seven-stages structural model by employing the interpretive structural modeling (ISM) technique. Through Matriced' Impacts Croise's Multiplication Appliquee a UN Classement (MICMAC) method, the DFs were categorized into "autonomous," "dependent," and "linking" segments. The results signify that "energy efficiency," "government incentives," "waste minimization," "resources conservation and recycling," and "water efficiency" were the top five DFs for GLSA. Further, the comparison with other countries reveals that the most significant driving force, "government incentives," is substantial for GLSA in the emerging economy of Pakistan. This article enhances knowledge of significant DFs for GLSA, furnishing a considerable source for managers, professionals, and policymakers to encourage GLSA at a wider level.

Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

Modelling the factors affecting Quality of Life among Indian police officers: a novel ISM and DEMATEL approach

Background

This study examines quality of life (QOL) of a sample of police officers in India. The concept of QOL includes well-being, social obligations, relationships of a person, and his association with environment. The study examines the factors on which QOL of police officers depend and their relationships with each other. The issues linked with QOL are important because they directly affect the individual's ability to maintain a healthy lifestyle and affect organizational performance in the long run. This study explores relevant factors that have an impact on the QOL of the employees of police department in India.

Method

In this paper, literatures review, ISM, MICMAC, and DEMATEL methodology have established eleven factors that impact the QOL of police officers in India. Mutual relations between factors have been established using the ISM approach to develop a model to represent these relationships. DEMATEL methodologies were used to analyze these factors.

Results

Results indicate that "fair compensation, work overload, workplace safety, and job stress" are the top-level factors that affect QOL of police officers.

Conclusion

The identification of factors and their mutual relationships that affect QOL are important for police officers and have to be dealt with according to their order of importance. The research model developed in this study shows how the factors of police officers' QOL are interrelated and presents the interrelationships among these factors. A comprehensive model depicting the relationships among these factors has been established, so that the QOL of police officers can be improved.

Artificial intelligence healthcare service resources adoption by medical institutions based on TOE framework

Objectives

This study used the Technology-Organization-Environment (TOE) framework to identify the factors involved in the decisions made by integrated medical and healthcare organizations to adopt artificial intelligence (AI) elderly care service resources.

Method

This study identified the Decision-making Trial and Evaluation Laboratory-Interpretive Structural Modeling (DEMATEL-ISM) method was used to construct a multilayer recursive structural model and to analyze the interrelationships between the levels. A MICMAC quadrant diagram was used for a cluster analysis.

Results

The ISM recursive structural model was divided into a total of seven layers. The bottom layer contained the four factors of High risk of data leakage (T1), Lack of awareness of the value and benefits of AI healthcare technology (T5), Lack of management leadership support (O1), and Government policies (E1). Having a low dependency but high driving force, these factors are the root causes of adoption by healthcare organizations. The topmost layer contained the most direct factors, which had a high dependency but the low driving force, influencing adoption: Competitive pressures (E2), Lack of patient trust (E5), and Lack of excellent partnerships (E7). Healthcare organizations are more concerned with technology and their environments when deciding to adopt intelligent healthcare resources.

Conclusion

The combination of the three methods of DEMATEL-ISM-MICMAC construction models provides new ideas for smart healthcare services for hospitals. The DEMATEL method favors the construction dimension of the micro-model, while the ISM method favors the construction dimension of the macro-model. Combining these two methods may reduce the loss of information within the system, simplify the matrix calculation workload, and improve the efficiency of operations while decomposing the complex problems into several sub-problems in a more comprehensive and detailed way. Conducting cluster analysis of the adoption determinants utilizing MICMAC quadrant diagrams may provide strong methodological guidance and decision-making recommendations for government departments, senior decision-makers in healthcare organizations, and policy-makers in associations in the senior care industry.

Antecedents and enablers of supply chain reconfigurability and their effects on performance

The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as the COVID-19 pandemic, demand uncertainty, and new technologies. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability, and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using "Matrice d'Impacts Croisés, Multiplication Appliquée à un Classement" (MICMAC) analysis. This article provides a better understanding of the six characteristics previously mentioned to improve the reconfigurability of supply chains by considering the interactions between their factors. Thus, this analysis helps managers to understand the characteristics that influence the change of the supply chain structure and those that enable changing the supply chain functions in order to optimize the supply chain reconfiguration process.

An integrated DEMATEL-MMDE-ISM approach for analyzing environmental sustainability indicators in MSMEs

The Micro, Small and Medium Enterprises (MSMEs) face numerous environmental challenges encompassing resource and energy conservation; waste generation and disposal; water and air pollution; and so on. As a result, it becomes critical to implement policies, strategies, and technologies that can help in reducing the adverse impacts of manufacturing activities on the environment. In this context, the current study identified 15 critical environmental sustainability indicators to assess the impact of manufacturing activities on the environment by taking a case study of lock manufacturing MSMEs. To understand the interdependence among the selected indicators, the study further utilizes an integrated DEMATEL-MMDE-ISM approach to analyze the inputs of industry professionals. The results of the study highlighted that green product design, which facilitates the product to be disassembled, reused, or recycled and are free from hazardous materials, plays a significant role in enhancing the environmental sustainability of the concerned industry. Green product design significantly affects 12 other indicators out of 15 under consideration; thus, incorporating green practices in the design and development of a product leads to significant improvement in environmental sustainability. The study is expected to aid decision-makers (industry practitioners and academic researchers) to identify strategic areas in order to achieve higher environmental sustainability in manufacturing organizations.

Analyzing the Stressors for Frontline Soldiers Fighting Against Coronavirus Disease 2019 Pandemic

This study aimed to analyze stressors to which medical staff is vulnerable due to the coronavirus disease 2019 (COVID-19) pandemic. It also imposes a hierarchy on complex relations among stressors for excavating underlying structure and builds a model of interrelationships contrasting reality. The design of this study comprises a literature survey, data collection from primary sources, and analysis. Stressors have been explored from within current published/unpublished literature and validated by experts through approval vote. Data were collected from the focus group (panel of experts), and interpretive structural modeling (ISM) was used as the research methodology. Findings of ISM are avowed through “cross-impact matrix multiplication applied to classification” (MICMAC) analysis. As a result of the literature survey, a list of stressors was generated, and a total of 19 stressors qualified as representative of the phenomenon. The results of ISM show that two stressors (i.e., “unavailability of proper personal protective equipment (PPE)” and “lack of proper communication”) emerged as the most critical stressors since they occupy the bottom of the model, whereas, four stressors (i.e., “anxious about isolation/quarantine,” “subject to violent crimes,” “feeling frustrated and powerless,” and “exhausting shifts/hours without clear end”) are relatively less critical since they occupy the top of the model. The rest of the stressors occupy the middle of the model and therefore, have moderate-severe effects on frontline soldiers. The results of MICMAC show that the stressor “subject to violent crimes” is classified in the dependent cluster and the remaining fall in the linkage cluster but no stressor falls in independent and autonomous. Overall results indicate that all stressors are relevant to the phenomenon under this study, but they are currently not settled. This study is invaluable for policymakers, frontline soldiers, researchers, the international community, and society since it provides a lot of new information that is helpful in refining strategies and combating influential stressors.

Structural Modeling on the Determinants of Effectiveness of SOPs Containing COVID-19 in Mass Gatherings

The study is aimed to analyze the determinants of the effectiveness of SOPs in mass gatherings for containing COVID-19. The overall design of the study involves a literature review, data collection by field survey, structural modeling, and analysis. The study is built on the experts' opinion of a focus group (representing people who recently participated in and are responsible for mass gatherings). The study uses the discussion of the literature review to identify the determinants, interpretive structural modeling (ISM) for developing and analyzing a structural model, and Matrice d'Impacts Croises Multiplication Appliquée a un Classement (MICMAC) for corroboration of results of the ISM/classification of determinants. From the literature review, a list of determinants is generated and verified by a panel of experts. The results of the ISM revealed that the determinants “legal environment of the country,” “practicability of SOPs,” “perceived benefit of adapting SOPs,” and “possibilities of avoiding gathering” occupied the top of the model, therefore, they are less critical determinants, whereas “nature of gathering” occupied the bottom of the model, and is thus the most critical determinant. The remaining determinants form the middle of the model, and are therefore moderately severe. The results of MICMAC show that the determinant “perceived benefit of adapting SOPs” is dependent, “nature of gathering” is independent, and all others are linked. The results of MICMAC implicitly substantiate the findings of the ISM. The overall results of the study show that “nature of gathering” is the key determinant. This research does not require a priori theory since it is a theory-building study that uses an inductive approach. It is based on real data and it is useful for local authorities, organizers, participants (attendees/visitors) of mass gatherings, health officials/regulators, researchers, and the community at large. This study has fundamental importance for planning and preparing for such events while ensuring the minimum risk of COVID-19 transmission.

Analyzing the Underlying Structure of Online Teaching During the COVID-19 Pandemic Period: An Empirical Investigation of Issues of Students

The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling (ISM) is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (MICMAC analysis) is used as a technique for classifying issues on the basis of driving-dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators' guidelines, stress of pandemic situation, and abrupt (not planned) start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 (i.e., connectivity issue, shy to use technology, lack of institutional guidelines, and stress of pandemic situation) are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues.

Enablers Supporting the Implementation of Knowledge Management in the Healthcare of Pakistan

Knowledge is considered to be an important resource; it is the source of competitive advantage. However, if knowledge is managed well with Knowledge Management (KM), then it becomes a source for sustainable competitive advantage for organizations. If KM is implemented in an organization, it would improve the organizational competitiveness, performance, and productivity, and facilitate the efficient use of resources. Due to intense competition in the global market, many organizations are moving towards the adoption of KM. The healthcare sectors of many developed countries have moved towards the implementation of KM because it can improve the procuring of knowledge from ongoing activities by the effective use of data repositories. Developing countries have now realized the potential and benefits of KM adoption. Pakistan is one of the developing countries that have recently shown an inclination towards the adoption of KM in its healthcare sector to improve performance of its healthcare. This study was composed of two main research phases. Firstly, the enablers of KM were reviewed from earlier studies. Secondly, interpretive structural modeling (ISM) and MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) techniques were used to show the interrelationships between KM enablers and driving and dependence power of each enabler. The application of ISM and MICMAC technique shows that policy incentive, long-term strategic planning, Information Technology (IT), and alignment of KM efforts with business strategy are the main enablers of KM adoption in the healthcare of Pakistan. Focusing on the identified enablers will help in the implementation of KM. Policy incentives can work as a catalyst to promote KM adoption in the healthcare of Pakistan.