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The purpose of this explorative research study is to focus on the implementation of semantic Web technology on agriculture domain of e-governance data. The study contributes to an understanding of problems and difficulties in implantations of unstructured and unformatted unique datasets of multilingual local language-based electronic dictionary (IndoWordnet).

An approach to an implementation in the perspective of conceptual logical concept to realization of agriculture-based terms and terminology extracted from linked multilingual IndoWordNet while maintaining the support and specification of the World Wide Web Consortium (W3C) standard of semantic Web technology to generate ontology and uniform unicode structured datasets.

The findings reveal the fact about partial support of extraction of terms, relations and concepts while linking to IndoWordNet, resulting in the form of SynSets, lexical relations of Words and relations between themselves. This helped in generation of ontology, hierarchical modeling and creation of structured metadata datasets.

IndoWordNet has limitations, as it is not fully revised version due to diversified cultural base in India, and the new version is yet to be released in due time span. As mentioned in Section 5, implications of these ideas and experiments will have good impact in doing more exploration and better applications using such wordnet.

Language developer tools and frameworks have been used to get tagged annotated raw data processed and get intermediate results, which provides as a source for the generation of ontology and dynamic metadata.

The results are expected to be applied for other e-governance applications. Better use of applications in social and government departments.

The authors have worked out experimental facts and raw information source datasets, revealing satisfactory results such as SynSets, sensecount, semantic and lexical relations, class concepts hierarchy and other related output, which helped in developing ontology of domain interest and, hence, creation of a dynamic metadata which can be globally used to facilitate various applications support.

The purpose of this paper is to examine the impact of augmented reality (AR) on retailing by conducting thematic analysis on variables studied in the existing literature.

The data set includes 232 variables studied in 35 research papers, collected using well-defined search and inclusion criteria. Thematic analysis is used to identify patterns in the data set.

The eight themes emerging from the analysis are arranged in the form of a conceptual framework to model the decision-making process of users. The position of themes in the model is determined by the most dominant variable type in the theme and by employing the technology acceptance model as the reference paradigm.

The current review contributes to the advancement of literature by setting a research agenda for scholars working in the field of consumer behavior and human–computer interaction. Future research should improve the generalizability of the research by replicating the method and testing the conceptual framework on other immersive technologies.

Marketers should incorporate AR technology into their experiential marketing strategies. Since integrating and managing AR technology requires expertise, organizations are advised to make use of existing toolkits or collaborate with technology companies to develop their offerings.

To maintain the uniqueness of the current study from other papers focusing on existing research done in this area, this review considers only studies using statistical techniques to study consumer behavior pertaining to AR in retail. The study uses an unconventional method for identifying patterns in the existing literature by employing theories and frameworks as the basis of classification.

The study constructs a composite indicator to rank macroeconomic performance of countries and a separate composite indicator to rank countries by inequality using the TOPSIS methodology of Multiple Criteria Decision-Making Analysis. The intuitive idea of TOPSIS is to formulate an ideal solution with respect to each individual policy variable; the relative rank of any country is then determined, using a suitable distance metric, such that the best performer simultaneously has the shortest distance from the ideal solution and the farthest distance from the non-ideal. It uses the composite indicator based rankings together with the KOF Globalization Index and sub-indices based rankings to examine the overall relationship between globalization and macroeconomic performance of countries and reduction in inequality; the impacts of trade and financial globalization for 1990–2018 across countries and groups of the globe. It shows that though highly correlated with growth, globalization may not necessarily lead to an improvement in overall macroeconomic performances of countries when one also takes into account unemployment and inflation. Economic globalization is seen here to mostly coincide with rise in income inequality. Observations also support the fact that countries, even if they are not highly integrated may reap sufficient benefits of globalization for macroeconomic performance and inequality diminution given supportive policies.

In the post-WTO era, the volume of international trade has grown in a good amount in India. At the same time, the continuous lowering and removing of the trade barriers of different forms create several impacts on poverty and inequality. In this chapter, we tried to capture the issues of inequality, specially the gender inequality, which has worsened a lot in the last two decades. In one side, trade openness enhanced the growth, but at the cost of increasing inequality. Theil index and Atkinson index both show an increasing trend of inequality. The Gender Inequality Index (GII) and the Inequality-adjusted Human Development or Gender Development Indices are also showing increasing inequality. The state-wise analysis of such inequality indices is varying a lot over the study period. This chapter throws some insight into these issues and concludes that in the post-WTO era income inequality has increased a lot with a very few exceptions. In some states (like Maharashtra, Gujarat, Karnataka, and Punjab) only export have increased the employment in the unorganized sectors. The study concludes that exports have generated additional employment and incomes in the economy, but these gains have not trickled down to the poor. The study is confined to Indian cases only and covers the time period 2000–2001 to 2018–2019.

The financial system of an economy, especially banking, facilitates efficient allocation of resources from savers to borrowers for productive investments, and thus promotes economic growth. State-wise bank credit in India shows a growing divergence, despite the aim of central planning to reach a degree of convergence in macroeconomic performance over time. This chapter analyzes how diverging bank credit affects macroeconomic performances of the Indian states, through an alternative approach of composite indicators-based rankings of states adopting the methodology of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) that is used in operations research or more specifically MCDM (multiple criteria decision-making). A composite indicator of the states’ annual macroeconomic performances has been constructed taking indicators of output growth, per capita state domestic product, inflation, and fiscal indicators for years 2006–2018. States are ranked by both macroeconomic performance and bank credit to states, and the correlation between the two indicators, known in the literature to be interlinked,is studied here to understand how the availability of credit or lack of it has influenced State level macroeconomic development in India. The results thus show that wealthier and better performing states continue to attract the larger chunk of bank credit, while weaker states have not been able to catch up. An important policy implication would be to place even more emphasis on higher levels of credit growth for weaker states, particularly infrastructure credit, to achieve a degree of income convergence throughout the Indian economy.