Possible Opportunities in Face Mask Manufacturing During the COVID-19 Pandemic

COVID-19 has been primarily regarded as a respiratory disease, and until a safer and effective treatment or vaccine becomes available, the prevention of COVID-19 may continue through interventions based on non-pharmaceutical measures such as maintaining of physical distances and use of personal protective equipment like facemasks, etc. Therefore, an attempt was made in this study to explore the drawbacks with the presently available facemasks for protection from COVID-19 viruses in the state of Odisha in India, and also to explore the possible opportunities for further development of these facemasks. The associated discomforts; strength, weaknesses, opportunities, and threats (SWOT) analysis of existing facemasks in Odisha; possible opportunities for “Make in India” of these facemasks; along with safer use have been analyzed with the help of interpretive structural modelling (ISM) approach followed by MICMAC analysis.

Modelling the abstract knots in supply chains using interpretive structural modelling (ISM) approaches: a review-based comprehensive toolkit

PurposeThis study endeavours to (a) develop a comprehensive interpretive structural modelling (ISM) toolkit containing sufficient details about the suitability and procedural aspects of each ISM approach and offer points of reference for budding researchers, (b) highlight the compatibility of ISM approaches with other qualitative and quantitative approaches, and (c) chalk-out an agenda for future research.Design/methodology/approachThis study is based on an extensive review of 74 studies where researchers have used one or more ISM approaches. These studies span across the different industry sectors.FindingsThere exists a huge void in terms of the methodological synthesis of ISM approaches. ISM approaches are frequently used in sync with other qualitative and quantitative approaches. Furthermore, it highlights the need of improving the robustness of the proposed ISM models by sharing the critical details of research process.Research limitations/implicationsBeing a review-based work, it could not illustrate the discussed ISM approaches with real data. However, it offers a research agenda for the prospective researchers.Practical implicationsThe prerequisites, pitfalls, suitability and the procedural aspects of various ISM approaches contained in this toolkit are equally useful for the academicians as well as practitioners.Originality/valueIn the absence of a synthesized framework, this study contributes a comprehensive ISM toolkit which will help the researchers to choose a suitable ISM approach in a given case.

Application of Interpretative Structural Modeling (ISM) to Determine Port Waste Management Strategies for African Swine Fever (ASF) Prevention at Tanjung Priok Port

African Swine Fever (ASF) is one of the infectious diseases affecting swine with high mortality rate. Disease transmission occurs direct and indirect. Indirect transmission through feed, virus contaminated object and swill feeding produced by ships. Ships berthing in the port of Tanjung Priok mostly comes or transits from a country which ASF exist. Among those ships, some discharge their garbage and take over into the final dumping site without any further treatment. There are many institution and a third parties involved in garbage management in the port of Tanjung Priok. This research aims is to identify an obstacle, actors and strategies in managing garbage from the ships to prevent ASF spread in the port of Tanjung Priok using Interpretative Structural Modelling (ISM). The results of this research shows the biggest obstacle in managing garbage from the ships, in order to prevent ASF spread in the port of Tanjung Priok is the absence of standard operating procedures (SOP), The most important actor is Indonesia Port Corporation II and the most important strategy is develop an integrated SOP for ship waste management. is to develop an integrated SOP for ship waste management.

Sustainability Factors Affecting the Implementation of Design for Dis-assembly and Re-manufacturing Principles in Automobile Sector Using ISM

With the automobile sector pacing the tracks among their competitors to lead the market and adopting eco-friendly technologies, a much economic and vital field of making use of the manufactured product beyond its useful life span is widely neglected. This paper throws light on the necessity for implementing and highlights the various reasons for which these guidelines have not come to the attention of the responsible organizations including law making agencies, automobile manufacturers and as well the consumers. An interpretive structural modelling analysis is made to point out ten driving factors in consultation with various experts from the relevant fields and the results provide guidance to how far the idea of design for dis-assembly and re-manufacturing has sought the world for the sustainability of the automobile manufacturers in the industry, for the days to come.

Lean Enhancement by Application of Total Interpretive Structural Modelling

Prioritizing of factors for effective lean manufacturing poses a challenge to management due to complexities in interrelationships. Diligent understanding of measures of lean manufacturing assumes great importance. Essential manufacturing flexibilities take care of uncertainties driven by dynamics of the market. Interrelationship between factors of manufacturing flexibility and lean manufacturing adds to complexity. Judicious analysis of these factors is imperative to understand their effect on lean manufacturing. Total interpretive structural modeling methodology is used for establishing relationships among the factors affecting lean performance. Case studies have been carried out and TISM is applied to understand the dynamism of factors. Study brings out how the organization of the companies and level of automation help in understating the driving and dependence power. The study helps in understanding the influence of hierarchy and level of factors identified by TISM technique on lean performance as also the factors which merit attention of top management to achieve better results

A TISM and MICMAC analysis of factors during COVID-19 pandemic in Indian Apparel Supply Chain

The objective of this study is to explore the challenges faced by the Indian apparel supply chain in the wake of COVID-19 to identify the factors that are being affected and build a multilevel hierarchy model to prioritize the factors and understand their inter-relationships. An intensive literature review was conducted and many experts from apparel supply chain were consulted. The study was conducted by the help of a survey sent to these experts from different echelons in the apparel industry. The data was then analysed using Total Interpretive Structural Modelling (TISM). The “Difficulty in export order fulfilment” factor is found to be the most sensitive factor which means that it is present in the TISM model hierarchy in a place that it is affected by most of the factors and in-turn impacts factors like operational cost, change in marketing strategy, change in consumer buying pattern, which impact Profitability and Cut-off in employment. “Cut-off in employment” is found to be most impacted by all other factors in TISM model.

Analysing the impact of artificial intelligence on the competitiveness of tourism firms: a modified total interpretive structural modeling (m-TISM) approach

PurposeThis study explores the variables that drive the impact of artificial intelligence (AI) on the competitiveness of a tourism firm. The relationship between the variables is established using the modified total interpretive structural modelling (m-TISM) methodology. The factors are identified through literature review and expert opinion. This study investigates the hierarchical relationship between these variables.Design/methodology/approachThe modified total interpretive structural modelling (m-TISM) method is used to develop a hierarchical interrelationship among variables that display direct and indirect impact. The competitiveness of a tourism firm is measured by investigating the effect of variables on the firm's financial performance.FindingsThe study identifies ten key factors essential for analysing the impact of AI on a firm's competitiveness. The m-TISM methodology gave us the hierarchical relationship between the factors and their interpretation. A theoretical TISM model has been constructed based on the hierarchy and relationship of the elements. The elements that fall in Level V are “AI Skilled Workforce”, “Infrastructure” and “Policies and Regulations”. Level IV includes the elements “AI Readiness”, “AI-Enabled Technologies” and “Digital Platforms”. Elements that fall under Level III are “Productivity” and “AI Innovation”. Level II and Level I comprise “Tourist Satisfaction” and “Financial Performance”, respectively. The levels indicate the elements' hierarchical level, with Level I the highest and Level V the lowest.Research limitations/implicationsTourism and AI scholars can analyse the given variables by including the transitive links and incorporate new variables depending upon future research. The m-TISM model constructed from literature review and expert opinion can act as a theoretical base for future studies to be conducted by researchers.Practical implicationsManagement/Practitioners can focus on the available characteristics and capitalise on them while working on the factors lacking in their organisation to enhance their competitiveness. Entrepreneurs starting their own business can utilise the elements in understanding the ecosystem of strengthening a firm's competitiveness. They can work to improve on the aspects which are crucial and trigger the impact on competitiveness. The government and management can devise policies and strategies that encompass the essential factors that positively impact the competitiveness of the firms. The approach can then be looked at with a holistic approach to cater to the other related components of the tourism industry.Originality/valueThis study is the first of its kind to use the modified TISM methodology to understand the impact of AI on the competitiveness of tourism firms.

Clinical grade ACE2 effectively inhibits SARS-CoV-2 Omicron infections

The recent emergence of the SARS-CoV-2 variant Omicron has caused considerable concern due to reduced vaccine efficacy and escape from neutralizing antibody therapeutics. Omicron is spreading rapidly around the globe and is suspected to account for most new COVID-19 cases in several countries, though the severity of Omicron-mediated disease is still under debate. It is therefore paramount to identify therapeutic strategies that inhibit the Omicron SARS-CoV-2 variant. Here we report using 3D structural modelling that Spike of Omicron can still associate with human ACE2. Sera collected after the second mRNA-vaccination did not exhibit a protective effect against Omicron while strongly neutralizing infection of VeroE6 cells with the reference Wuhan strain, confirming recent data by other groups on limited vaccine and convalescent sera neutralization efficacy against Omicron. Importantly, clinical grade recombinant human soluble ACE2, a drug candidate currently in clinical development, potently neutralized Omicron infection of VeroE6 cells with markedly enhanced potency when compared to reference SARS-CoV-2 isolates. These data show that SARS-CoV-2 variant Omicron can be readily inhibited by soluble ACE2, providing proof of principle of a viable and effective therapeutic approach against Omicron infections.

Analisis Kendala Pembelajaran Daring PAUD dan SD dengan Pendekatan Interpretative Structural Modeling (ISM)

Pembelajaran daring merupakan pembelajaran yang menggunakan model interaktif berbasis internet. Pembelajaran daring adalah program untuk mengatur kelas belajar di jaringan untuk mencapai kelompok dengan jangkauan yang lebih, analisis kendala pembelajaran daring pada Pendidikan Anak Usia Dini (PAUD) dan Sekolah Dasar (SD) bertujuan untuk membuat prioritas kendala pembelajaran daring dan mencari solusi dari permasalahan tersebut. Metode penelitian yang digunakan dalam penelitian ini adalah metode penelitian deskriptif kualitatif menggunakan sofware Interpretative Structural Modelling (ISM). Interpretative Structural Modelling (ISM) merupakan salah satu metode yang baik dalam menstrukturkan hingga mendesain hirarki permasalahan yang bersifat abstrak dan kualitatif serta dapat menggambarkan pemetaan masalah dalam bentuk kuadran dan strukturisasi masalah sesuai dengan prioritas permasalahan. Berdasarkan hasil penelitian kendala utama dalam proses pembelajaran daring adalah komunikasi, gagap teknologi dan motivasi belajar.