The COVID 19 is a pandemic having an epidemic nature influencing the human health and economy in a global level. The major limitation to overcome the issue is the lack of potential vaccines or effective medicines to treat or control the disease. Considering the shortness of time to act, the purpose of the paper was to identify and categorise the climatic, socio-biological factors that influence the global super-spread of the epidemic using a theory building approach, ‘Total Interpretive Structural Modelling’ (TISM). MICMAC analysis of the identified factors, based on their interdependence categorized the triggering factors, air temperature, humidity, age, airflow and ventilation, responsible for the increased mortality rate of COVID 19 compared to SARS and MERS. So the model explains why the temperate countries of similar climatic zones and aged people are more vulnerable. It also predicts the susceptibility of countries based on their geographic locations and upcoming climatic conditions which were found to be influential in sustaining longevity and aerosol spread of the virus. Since many of these factors remain unaltered or out of human control, the linkage factors identified in this paper; change in host behaviour and number of contacts can be given priorities in order to overcome the situation. Furthermore, this is the first attempt made to understand epidemiological characteristics of COVID 19 using TISM approach.

Purpose: The purpose of this paper is to identify, analyze and develop a model to measure the interactions among different factors of organizational readiness for change in service sector specific to healthcare organization. The total interpretive structural modeling (TISM)-based readiness for change is to build a theoretical framework to understand the mutual interactions among the factors and to identify the driving and dependence power of these factors. Design/methodology/approach: TISM is used to identify factors that contribute to analyze the readiness state before starting a change implementation process in healthcare. Matrice d’Impacts croises-multiplication applique´ a classement analysis is used to find the driving and dependent factors of change in healthcare. Findings: This paper identified 12 factors of readiness for change from literature review followed by expert interview to understand the inner connection of factors and study inner relationships. The result says that state of affairs, recent trends in healthcare sector, technology advancement and interdependence among departments are key factors for readiness of change. Research limitations/implications: This research mainly focused on readiness factors for change in the healthcare sector. Practical implications: This study will be useful for researcher and practitioners to understand the readiness factors for change. Originality/value: In this research work, TISM-based readiness for the change framework structural model has been proposed for healthcare organizations which is a new effort in the area of organizational change management in this sector.

Healthcare organizations implement lean practices to improve service quality and competitive advantage. It eliminates the process waste leading to improved healthcare service at a reduced cost. This study attempts to analyse the relationship among the factors that influence implementation success using Interpretive Structural Modelling (ISM). Its contribution to the body of knowledge is twofold. First, it provides a hierarchical structure displaying the driving and dependent factors. Second, it ranks the factors affecting the implementation success based on the degree of influence. The factors have been identified by taking inputs from existing literature and expert opinion. The conceptual relationship among the factors has been determined by conducting a survey among healthcare professionals and the final analysis has been done using ISM. The findings suggest that leadership is the most crucial factor for a successful implementation. Apart from this, having a clear goal in advance for the project and adequate training of the workforce are instrumental in lean intervention. Finally, limitation and future research avenues have been outlined to extend the current study.

The global risks report of 2020 stated, climate-related issues dominate all of the top-five long-term critical global risks burning the planet and according to the report, “as existing health risks resurge and new ones emerge, humanity’s past successes in overcoming health challenges are no guarantee of future results.” Over the last few decades, the world has experienced several pandemic outbreaks of various pathogens and the frequency of the emergence of novel strains of infectious organisms has increased in recent decades. As per expert opinion, rapidly mutating viruses, emergence and re-emergence of epidemics with increasing frequencies, climate-sensitive vector-borne diseases are likely to be increasing over the years and the trends will continue and intensify. Susceptible disease hosts, anthropogenic activities and environmental changes contribute and trigger the ‘adaptive evolution’ of infectious agents to thrive and spread into different ecological niches and to adapt to new hosts. The overarching objective of this paper is to provide insight into the human actions which should be strictly regulated to help to sustain life on earth. To identify and categorize the triggering factors that contribute to disease ecology, especially repeated emergence of disease pandemics, a theory building approach, ‘Total Interpretive Structural Modeling’ (TISM) was used; also the tool, ‘Impact Matrix Cross-Reference Multiplication Applied to a Classification’ analysis (MICMAC) was applied to rank the risk factors based on their impacts on other factors and on the interdependence among them. This mathematical modeling tool clearly explains the strength, position and interconnectedness of each anthropogenic factor that contributes to the evolution of pathogens and to the frequent emergence of pandemics which needs to be addressed with immediate priority. As we are least prepared for another pandemic outbreak, significant policy attention must be focused on the causative factors to limit emerging outbreaks like COVID 19 in the future.