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This paper aims at analyzing the determinants of access to relief under social assistance programs among rural households during COVID-19 outbreaks in India.

The study is based on the data of COVID-19-Related Shocks Survey, which covered 5,200 rural households across 6 states of India namely Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh Rajasthan, and Uttar Pradesh. The access to relief has been assessed as relief-in kind (RIK) as a free special package of wheat, rice, and pulses, supplied through the public distribution system; and direct benefit transfer (DBT) in cash under the Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) Yojana and the Pradhan Mantri Jan-Dhan Yojana (PMJDY). The association between demographic profiles of rural households and access to relief has been analyzed using the chi-square test. Further, marginal effects have been estimated to assess the determinants of rural households' access to relief.

The results show a significant association between types of relief vis-à-vis demographic profiles of the rural households. A significant difference in access to relief among rural households is also evident across the states. Further, the analysis of the marginal effects indicates that female-headed households belonging to lower social class, depending on non-agricultural occupation with lower income, belonging to below poverty line families and seeking wage employment, are more likely to access relief as food grains; whereas male respondents with lower age, belonging to lower-income quartile with memberships in Self Help Groups are more likely to access the cash benefit transfers.

The COVID-19 pandemic has affected the food security and livelihood of many across the globe, which necessitated provisioning a package of support to everyone, particularly rural poor households. The World Bank undertook the COVID-19-Related Shocks Survey to provide a quick policy response for managing the risk of COVID-19 outbreak effectively. The results of this study provide timely insights for developing an effective relief strategy for rural households during a crisis.

There is limited investigation on access to relief by rural households during the COVID-19 outbreaks and factors affecting the access to relief in terms of cash and kind. This study has utilized a reliable data source to analyze the access of relief packages by the rural communities during the coronavirus outbreak.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0632.

Blockchain is an evolving technology that has an impact on a variety of industries and related operations including food supply chain. There are several challenges associated in the implementation of blockchain in the food supply chain. As a result, the goal of this research is to identify and analyse the barriers associated with the implementation of blockchain in food supply chains.

A comprehensive literature review is conducted to identify 16 primary barriers associated with the implementation of blockchain technology in the food supply chain and experts finalise these identified barriers and further categorise them into four groups. Furthermore, the best worst method is used to prioritise the finalised barriers.

The findings suggest that “technological barriers” and “organisational barriers” are primary barriers among the identified barriers for the implementation of blockchain. These barriers could be mitigated through supply chain collaboration, efficient blockchain technology development through research and development, and increasing technical competence.

In terms of limitation, there is a possibility that some barriers were overlooked in the literature review process, and expert judgement might be prejudiced. This paper examines the blockchain implementation in the food supply chain, to assist policymakers in overcoming these barriers and ensuring effective adoption.

This study focuses on the effective implementation of blockchain technology in the food supply chain in the context of emerging economies.

This study aims to introduce a modern higher efficiency predictor–corrector iterative algorithm.

Furthermore, the efficiency of new algorithm is analyzed on the based on Chun-Hui He’s iteration method.

In comparison with the current robust algorithms, the newly establish algorithm behaves better and efficient, whereas the current existing algorithm fails or slows in the considered test examples.

The modified Chun-Hui He’s algorithm has great practical implication in numerous real-life challenges in different area of engineering, such as Industrial engineering, Civil engineering, Electrical engineering and Mechanical engineering.

The paper presents a modified Chun-Hui He’s algorithm for solving the nonlinear algebraic models exist in various area.

This study aims at modelling the enablers of dairy supply chain (DSC) in Indian context.

Interpretive structural modelling (ISM) approach has been used to model the enabler of dairy supply chain. The opinion has been taken from the industry experts and experienced academicians. Further, Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) used to classify the enablers based on driving and dependence power.

Findings show that stakeholder trust and top management support/leadership are the very crucial enablers in dairy supply chain; they are at a lower level of hierarchical structure and work as primary enablers to development of DSC. While customer satisfaction and financial performance are at top of the digraph, it shows these enablers are the outcome of a smooth supply chain. The MICMAC analysis suggests that the identified enablers are largely classified into dependent and independent enablers; there are no autonomous enablers in the dairy supply chain.

The study can aid businesses in the dairy processing industry in managing demand fluctuations, enhancing product quality, implementing effective information systems and adapting procedures, thereby enhancing supply chain performance.

There is very limited study on enablers of the dairy supply chain in general, while in the Indian context, there is no specific study on modelling the enablers of dairy supply chain.

The purpose of the study is to examine the obstacle in doing business and determinants of credit adoption by the textile enterprises in India.

The study is based on World Bank’s Enterprises Survey, there are 571 enterprises involved in textile business. The enterprises survey has response on wide range of business obstacles which are categorized under three broad categories, namely, access to resource, business regulations and market externalities. Chi-square test and analysis of variance (ANOVA) have been used to examine the significant difference among firm’s profile and perceived business obstacles across the firm size. Furthermore, binary logistic regression model has been applied to explore the determinants of credit adoption by textile enterprises.

A statistically significant difference has been found in size of firms and legal status nature of establishment, gender of top manager, main product market and credit adoption from financial institutions. Majority of small- and medium-sized enterprises (SMEs) are sole proprietorship firm while large enterprises are limited partnership firms. Similarly, large enterprises have relatively more female as a top manager and international market for their product. ANOVA reveals equal degree of obstacles in doing textile business across the firm size. The logistic regression coefficient and marginal effects reveal that firm size, main market,gender of owner, number of establishment in the firms positive and significantly affects the credit adoption by 3 textile enterprises.

The study has some policy implications for various stakeholders such as textile business managers and promoters, government, investors and bankers for entrepreneurship development in textile sector. The study suggests that the government should incentivize small- and medium-sized businesses to increase their exports. The results show that despite government efforts to finance SMEs, fewer SMEs are receiving both short- and long-term credit. To help SMEs in the textile industry overcome financial difficulties and expand their main product market to both domestic and international levels, a soft loan should be provided based on the characteristics of textile enterprises.

The present study suggests the evidence-based understanding of textile business environment. The value and uniqueness of this study is to explore an ease of business textile sector using comprehensive enterprises survey data of World Bank.

The purpose of this paper is to analyze the characteristics of agribusiness firms in India, China and Pakistan, as well as the challenges they face in doing business.

This study is based on the World Bank’s Enterprises Survey (WBES) data. The survey was carried out through a questionnaire survey from the owner and top managers of 716, 247 and 174 agribusiness from India, Pakistan and China, respectively. This enterprises survey has comprised the information regarding the wide range of firms’ characteristics and 16 parameters of business obstacles. Simple statistical tools such as chi-square and analysis of variance have been used to analyze the data.

Chi-square test shows the statistically significance difference in firms’ characteristics across agribusiness firms of India, China and Pakistan. Chinese firms are better in terms of having an international quality certification, own websites and getting credit. In Pakistan, access to land for agribusiness is an obstacle while for India and China, it is easy to acquire land for agribusiness purposes. In Pakistan, tax rate and political stability is a moderate obstacle while in India and China, it is a minor obstacle in agribusiness. Labor regulation does not perceive any considerable obstacle in doing business in India and Pakistan.

This study provides an understanding of differences in the agribusiness environment in emerging economies such as India, Pakistan and China based on WBES data. This study can be helpful for agribusiness managers and government policymakers for promoting agriculture-based entrepreneurship.

It is the first attempt to compare the profile of agribusiness firms in growing Asian economies such as India, Pakistan and China, as well as perceived business hurdles, using a comprehensive enterprises survey data of World Bank.

The rate of cesarean sections has been rapidly increased in the last few decades in all the developing as well as developed countries. The rate of cesarean sections determined by the World Health Organization has been crossed by many countries, like Brazil, India, China, USA, Australia, etc. Similarly, this rate has also increased in Pakistan. The purpose of this paper is to explore and identify the factors that are responsible for the rising rate of cesarean sections in Pakistan.

These factors are categorized under medical and non-medical factors. The medical factors include the obesity of mother, age of mother, weight of the baby, umbilical cord prolapse, fetal distress, abnormal presentation, dystocia and failure to progress. The non-medical factors include financial incentives of doctors, time convenience for doctors, high tolerance to surgery, patient’s preference toward cesarean section, private hospitals, public hospitals, income status of patients, rural areas, urban areas and the education of patients. To identify the critical factors, data have been collected and a multi-criteria decision-making technique, called Decision Making Trial and Evaluation Laboratory, is used.

The result shows that the medical factors that are responsible for the rise in the rate of cesarean sections are umbilical cord prolapse, age of mother and obesity of mother. On the other hand, the non-medical factors that are the reasons for the increase in cesarean sections are the large number of private hospitals and the unethical acts of the doctors in these hospitals, preference of patients, and either the unavailability of doctors or poor conditions of hospitals in rural areas.

Cesarean section is an important surgical intervention and is considered to be very essential in the cases of existing as well as potential medical problems to the mother or the baby. Cesarean section is also performed for non-medical reasons. In Pakistan, the number of private hospitals has increased and these hospitals provide good health care. However, these hospitals do not work under the rules and regulations set by the government. The doctors in private hospitals perform unnecessary cesarean sections in order to fulfill the demands of private hospital’s owners. In addition to this, it is also found that, nowadays, most women prefer to give birth through cesarean section in order to eliminate the pain of normal vaginal delivery.

This study aims at identifying a set of determinants that affect halal food purchase intention and measures the relative ranks of these determinants in purchasing halal food among Muslim consumers in India.

Interpretive structural modeling (ISM) approach has been employed in the research, which is an expert opinion-based approach. The opinions of experienced academicians and marketing professionals have been recorded for reaching to the conclusions. Matrice d' impacts croises multiplication appliqué an classement (MICMAC) analysis has also been applied to examine the driving and dependent power of these determinants.

Driver power–dependence matrix reveals that although knowledge of halal and attitude are weak drivers, yet they are strongly dependent upon other determinants. These two variables are at the top of the ISM digraph hierarchy. Food safety and halal labeling have strong driving power, as well as strong dependence. Three determinants, namely brand origin, religiosity and price, have strong driving powers and weak dependence. These variables lay at the bottom level of the ISM model.

This study provides a better understanding of the determinants of halal food purchase intention. This will help the marketers for making appropriate and effective product design and other marketing strategies suited to the needs of the consumer.

This is the first study that examines the interrelationships between determinants and relative rank of these determinants in halal food purchase, using ISM approach and MICMAC analysis.

This paper aims to examine and discuss the factors affecting consumers' purchase intentions for ice cream in India.

This study is based on a primary survey of 340 respondents from India, collected through a well-structured questionnaire. The data has been analysed using partial least square-based structural equation modelling (PLS-SEM). The theory of planned behaviour (TBP) has been used to identify the determinants of the purchase intention of ice cream.

The measurement model shows that the constructs of the model have adequate convergent and discriminant validity. The findings of the structural model show the positive and significant impact of subjective norms, perceived behavioural control, and trustworthiness on attitudes and purchase intentions for ice cream. In addition, estimates also revealed that attitude has significant implications on purchase intention.

The study provides insight into the factors that influence ice cream purchase intentions in India. Corporate strategy makers and advertising managers who work for ice cream brands can look at the study to figure out how to market their products to get more customers.

The novelty and value of this study lie in choosing an unexplored product (ice cream) whose demand is continuously increasing. Perhaps this is the first study in an emerging economy like India to consider an extended version of the TPB by including health consciousness and trustworthiness to establish the relationship between ice cream purchase intention and health consciousness.

Cement industry for both developed and developing countries is important from the economic point of view. It is playing a vital role in economic development of a developing country like Pakistan. However, these industries are posing threat to the environment, human health and plant species. The purpose of this paper is to identify the most critical factors of cement industry that have a negative impact on the environment, human health and plant species in the context of Pakistan.

The factors are categorized into air pollution, noise pollution, soil pollution, human health and plant species. These factors are categorized on the basis of previous literature and environmental safety reports. Air pollution is caused by iron and sulphur while noise pollution is mainly caused by crusher room and rotatory kiln end. The soil is being polluted by zinc and lead while human health and plant species are being damaged by sulphur dioxide and nitrogen dioxide. For the analysis purpose, a multi-criteria decision-making (MCDM) technique, i.e., decision-making trial and evaluation laboratory (DEMATEL) is used.

The result shows that the major cause of air pollution is “sulphur” while “crusher room and rotatory kiln end” are responsible for noise pollution. On the other hand, “mercury” is responsible for causing soil pollution while human health and plant species are influenced by the toxic effect of “nitrogen dioxide.”

The results obtained are specific to cement manufacturing industry of Pakistan and cannot be generalized for any other manufacturing sector.

The proposed methodology shows the most critical factors toward which concertation should be given for mitigating their impact. This study will help the government and the cement industry to focus on all those elements that are the most responsible for causing different types of pollution.

No such work is reported in previous research that proposes a framework using DEMATEL technique for analysis of critical factors of cement industries that have a dangerous impact on the environment and human health, especially in a developing country, like Pakistan.