Modelling the factors influencing the service quality in supermarkets

The Covid-19 has shifted the face of many markets including e-commerce and online business with many bottlenecks to be cleared. The last-mile delivery project has the greatest effect on all types of e-commerce companies because it has many consumer touchpoints as well as the Covid-19 pain points. Due to these interconnected issues, the delivery projects itself requires modern solutions. The purpose of this paper is to identify, analyse and categorize the major factors that affect the last mile delivery projects in e-commerce, food sector, retail sector and so on using total ınterpretive structural modelling approach during the Covid-19. Ten major factors are identified from literature review, and expert opinions are collected from multiple organizations that are involved in the last mile delivery projects. The results indicate that types of goods, achieving routing efficiency and meeting fulfilment timeline are the key factors for last mile delivery projects during the time of Covid-19. This study helps the managers to identify the key factors and to focus on these factors for the successful implementation of last mile delivery project.

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“…MICMAC involves the categorization of the factors identified into four classes (Suresh et al 2019a , b , 2021b , c ) as shown in Table 5 .…”

Section: Resultsmentioning

confidence: 99%

A study on the influential factors of the last mile delivery projects during Covid-19 era

Suguna¹,

Shah

Raj

et al. 2021

Oper Manag Res

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“…MICMAC involves classifying the factors into four different zones, namely, driving factors, autonomous factors, dependent factors and linkage factors [59][60][61][62][63][64]. The factors can be explained as below:…”

Section: Micmac Analysismentioning

confidence: 99%

Factors influencing the epidemiological characteristics of pandemic COVID 19: A TISM approach

Priyadarsini¹,

Suresh

2020

International Journal of Healthcare Management

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193

152

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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, sociobiological 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.

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“…The MICMAC analysis involves classifying the relevant causative factors into four different zones, namely: driving factors, autonomous factors, dependent factors and linkage factors [ [136] , [137] , [138] , [139] , [140] , [141] ] . The factors for this article were classified as: Autonomous factors (Zone-I): Factors that have weak dependence power and weak driving power are known as autonomous factors.…”

Section: Resultsmentioning

confidence: 99%

What can we learn from previous pandemics to reduce the frequency of emerging infectious diseases like COVID-19?

2020

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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.

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Modelling the factors influencing the service quality in supermarkets

Cited by 57 publications

References 53 publications

A study on the influential factors of the last mile delivery projects during Covid-19 era

A study on the influential factors of the last mile delivery projects during Covid-19 era

Factors influencing the epidemiological characteristics of pandemic COVID 19: A TISM approach

What can we learn from previous pandemics to reduce the frequency of emerging infectious diseases like COVID-19?

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