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This study attempts to investigate the interrelationship between choice-based educational achievement and employability prospects across the skill-based occupations amongst the youth in India.

This study relies on the use of National Sample Survey (NSS) data on employment and unemployment for the 68th round (2011–2012) and the Periodic Labour Force Survey (PLFS) (2017–2018). To estimate the relative contributions of choice-based educational attainment affecting the skill-based employment of youth in a different category of occupations ( high/medium/low skilled), the multinomial logistic regression and its marginal effects have been used.

The study finds educational attainment both as an opportunity (improvising employability in the high and medium skill occupation) and a challenge (highest unemployment amongst the educated) while ensuring skill-based youth employability. Despite the growing enrolment of youth in education, youth from a general education background does not find sustained employability prospects in high-skill occupations.

Vocational education highlights a brighter employability prospect but the acceptability of the same amongst the youth needs a policy intervention.

Educational choices need an intervention based on market-driven apprenticeships and training.

The decline of overall employability in the low-skill occupation raises a threat to inclusive development as such youth results to Not in Employment, Education or Training (NEET), better identified as the unproductive economic youth.

This study attempts to investigate that “how far the choice of educational attainment (general/technical/vocational) is able to make youth a fit in the world of work?” in the Indian context, where the youth constitute the highest share in the population.

This paper aims to investigate student subgroups’ responses to the coercive digitalisation of teaching and learning processes during the pandemic. Respective variance is discussed in terms of digital inequality and is interpreted as a need to individualise teaching and learning and quality assurance practices.

This study uses data from surveys (N = 955) on student perceptions of the introduction of emergency digitalisation – an important aspect of higher education. The authors perform latent class analyses to identify student subgroups. The students were asked to rate digital learning processes and their overall learning experiences.

The identified student subgroups are proponents, pragmatics and sceptics of digitalised teaching and learning processes. These subgroups have different preferences with regard to teaching and learning modes of delivery, which implies the relevance of individualised educational services and respective quality assurance practices to reflections on improvement needs.

The data are from a single, typical German university; therefore, the scope of the results may be limited. However, this study enriches future research on the traits of student subgroups and students’ coping strategies in an ever-changing learning environment.

The findings may help individualise universities’ counselling services to enhance overall teaching performance and quality assurance practices in a digitalised environment.

The findings provide insights into students’ responses to the COVID-19 pandemic and its impact on teaching and learning. This paper enriches the research on student heterogeneity and relates this to development needs of quality assurance practice.

A number of studies have shown that internet banking (IB) implementation is not only determined by banks or government support, but also by perceptions and experience of IB users. IB studies have showed encouraging results from academics in developed countries. Yet little is known about the user adoption of IB in Lebanon. The purpose of this paper is to investigate the factors that may hinder or facilitate the acceptance and usage of IB in Lebanon.

A conceptual framework was developed through extending the unified theory of acceptance and use of technology (UTAUT) by incorporating two additional factors namely; perceived credibility (PC) and task-technology fit (TTF). A quantitative approach based on cross-sectional survey was used to collect data from 408 IB consumers. Data were analysed using structural equation modelling based on AMOS 20.0.

The results of the structural path revealed that performance expectancy (PE), social influence, PC and TTF to be significant predictors in influencing customers’ behavioural intention (BI) to use IB and explained 61 per cent of its variance, with PE was found the strongest antecedent of BI. Contrary to the UTAUT, the effect of effort expectancy on BI was insignificant. In addition, both BI and facilitating conditions were found to affect the actual usage behaviour and explained 64 per cent of its variance

This study would be helpful for bank managers and policy makers to explain the currently relatively low penetration rate of IB in formulating strategies to encourage the adoption and acceptance of IB by Lebanese customers, where IB is still considered an innovation.

This study is the first research that extend the UTAUT by incorporating two additional factors namely; PC and TTF to study the IB in the Lebanese context. This study contributes to the research on computer technology usage by looking at IB adoption and incorporation into the lives of customers via the BI to use and actual usage of IB in Lebanon.

Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous pollutant. Soil contaminated with petroleum hydrocarbons adversely affects the properties of soil. This paper aim to remove pollutants from the environment is an urgent need of the hour to maintain the proper functioning of soil ecosystems.

The ability of micro-organisms to degrade petroleum hydrocarbons makes it possible to use these microorganisms to clean the environment from petroleum pollution. For preparing this review, research papers and review articles related to petroleum hydrocarbons degradation by micro-organisms were collected from journals and various search engines.

Various physical and chemical methods are used for remediation of petroleum hydrocarbons contaminants. However, these methods have several disadvantages. This paper will discuss a novel understanding of petroleum hydrocarbons degradation and how micro-organisms help in petroleum-contaminated soil restoration. Bioremediation is recognized as the most environment-friendly technique for remediation. The research studies demonstrated that bacterial consortium have high biodegradation rate of petroleum hydrocarbons ranging from 83% to 89%.

Proper management of petroleum hydrocarbons pollutants from the environment is necessary because of their toxicity effects on human and environmental health.

This paper discussed novel mechanisms adopted by bacteria for biodegradation of petroleum hydrocarbons, aerobic and anaerobic biodegradation pathways, genes and enzymes involved in petroleum hydrocarbons biodegradation.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

This paper aims to examine the perception of parents regarding the role of children as influencers in family consumption decisions in India. The purpose is to support marketing practitioners in understanding the stages of children's influence in the family using the theoretical perspective of the resource theory approach.

This study is based on a Web survey approach. Primary data were obtained from a sample of 180 mothers of adolescent children in the age group of 13–18 years and residing in rural and urban areas of Delhi (India) by administering a bilingual (Hindi/English) pre-tested “structured non-disguised” questionnaire designed on the Google Forms.

The findings that emerged from this study and as supported by the relative theory approach revealed that Indian parents perceive their children to exert a significant influence in family buying decisions, children's influence varies across stages of the decision-making process and the type of product and children's influence in family buying decisions is moderated by family structure but not by family size. The results of this study extend interesting and practical implications for marketing practitioners in India and by extension in other similar countries while designing and implementing marketing mix strategies in respect of goods and services meant for children/family consumption.

The findings that emerged from this study and as supported by the relative theory approach revealed that Indian parents perceive their children to exert significant influence in family buying decisions, children's influence varies across stages of the decision-making process and the type of product, and children's influence in family buying decisions is moderated by family structure but not by family size. Results of this study extend interesting and practical implications for marketing practitioners in India and by extension in other similar countries while designing and implementing marketing mix strategies in respect of goods and services meant for children/family consumption.

The results of this study support the notion that children exert considerable influence in family buying decisions in India across products, hence constitute a viable target market for different products consumed not only by them but by other family members as well. It is, therefore, vital that marketers wishing to penetrate family and/or child product markets must identify the person in the family who is likely to be more involved in the buying process and the extent of his involvement to carve effective promotional strategies.

The finding that although Indian children are actively participating across various stages of the decision-making process and their influence is strongest at the purchase initiation stage has peculiar social implications whereby families may be exposed toward eco-friendly green products and sustainable ways of living through the children in rural as well as urban areas. Similarly, children were also found to be influential at the information search and evaluation stage; hence, the messages regarding social issues, gender equality and health issues, which are not yet openly discussed in Indian families, may be imparted through children for better coverage and effectiveness.

Children are an important part of the family; especially in the nuclear families, children are an apple of eye and central point of the discussion. The role of children in decision-making is also important because of the changing information system and modernization of the younger generation. This is an empirical study focusing on the areas not yet explored and examined in the context of a culturally distinct and emerging country in terms of the emergence of children as influencers in family consumption decisions in rural and urban Indian families.

The purpose of this paper is to explore the applicability of technology acceptance model (TAM) to explain the widespread acceptance and usage of social media (SM) for travel purposes by Indian outbound leisure travellers during their travel cycle.

The study has adopted a qualitative approach involving in-depth interviews of 30 respondents, who had taken at least one international vacation in the last 12 months. Content analysis was used to arrive at the conclusion.

Findings of the study are used to develop a conceptual model which upholds the validity of the TAM with perceived usefulness (PU) and perceived ease of use (PEU) as determinants of SM usage. The model has been extended to include perceived trust (PT) and social capital (SC) as important constructs to explain the travellers’ use of SM. Disposition readiness (DR) of the user towards SM was found to have an effect on all the four constructs.

Theoretically, this study suggests a modification to the existing TAM, which shows a unidirectional effect of PU and PEU on attitude. This study suggests that the effect would be bi-directional where the attitude (DR) of the traveller towards SM usage will affect PU and PEU. Furthermore, this study extends the TAM to include PT and SC as important constructs to explain SM usage by travellers. This study provides valuable insights into the hospitality and tourism sector which might help in further segmentation of travellers leading to more customised service offerings.

Crop suitability analysis is vital for identifying a piece of land’s potential for sustainable crop production and aids in the formulation of an effective agricultural management plan. This study aims to conduct crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops in Sirajganj district, a flood-prone area of Bangladesh, and recommend a suitable cropping pattern to mitigate the detrimental effects of flooding.

Various factors such as soil drainage, soil depth, soil moisture, soil texture, soil permeability, soil pH, erosion hazard, nutrient status and flooding risk were considered for this study. For all four crops, the weights of each factor were determined using the analytical hierarchy process approach, and the scores of each subfactor were assigned on the basis of favorable circumstances of crop cultivation. Using the weighted overlay analysis in the ArcGIS 10.3 environment, the crop suitability maps were generated and were divided into four suitable classes. Geographic information system integration of crop suitability for all the crops determined the suitable cropping pattern of the study area in Kharif and Rabi seasons.

A vast portion of the study area covering 64.80% of the total land is suitable for cultivating either rice or maize in Kharif season followed by either potato or wheat in Rabi season. Other suitable cropping pattern for Kharif and Rabi seasons found in the study area are rice-wheat, rice-wheat/potato, rice/maize-wheat and rice/maize-potato, which covers a little portion of the study area.

This research validates the suitable location of crop cultivation on the basis of flooding occurrences in the locality.