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Purpose: The purpose of the chapter is to highlight the game-changing potential of emerging technologies and how these will change the very face of companies cutting across industries. Our work also aims to highlight the converging point of these technologies and describes how these new-age inventions can be more effective if stakeholders adopt a collaborative approach rather than competing against each other.

Design/Methodology/Approach: Using real-world case studies, the chapter identifies the most significant emerging technologies heralding a new era of efficiency across business categories. This identification has been made based on both secondary data and expert interviews. The opinions of the domain and industry experts have also been included to select six emerging technologies for the analysis.

Findings: Based on secondary and primary data, the chapter has identified the five emerging technologies that are expected to change how businesses are run completely today. The technologies are: (1) Metaverse Platforms, (2) Blockchain Technology, (3) Non-fungible Tokens (NFTs), (4) Decentralised Finance, and (5) Cryptocurrency.

Research Limitations/Implications: By identifying emerging technologies and their application domains, the chapter contributes significantly to both the world of academia and practice. The research has important implications for scholars and practitioners as these stakeholders must prepare themselves to realise the maximum potential of these new-age inventions. Policymakers also need to contribute constructively so that the adoption and implementation of these technologies can be done smoothly and seamlessly.

Originality/Value: The research is unique in the sense that it identifies the most-significant emerging technologies and offers a constructive roadmap for stakeholders to integrate these new inventions into their functional procedures and operational mechanisms effectively and efficiently.

This paper aims to study the determinants of consumer purchasing behaviour of organic product in the emergent countries. These variables are related to products such as perception, attitude, motivation (health and environmental concern), implication and purchasing intention.

This paper is based on exploratory and confirmatory analysis that seeks to purify and to get a new scales structure. The study shows the effect of perception and motivation on the purchasing behaviour of the consumers who intend to buy an organic product. The authors used the structural equation modelling to confirm the different relationships.

Purchasing intention, implication and motivation (health and environmental concerns) have a strong direct and positive effect on the purchasing behaviour of organic products. However, the relationship between the motivation and the attitude, on the one side, and between attitude/purchasing intention and attitude/purchasing behaviour, on the other side, are not significant.

The research and investigation were carried out in a limited geographical zone (Tunisian country), on a specific category of products and on a particular sampling procedure by convenience.

The firm can adopt an efficient green strategy that allows it to ensure a good segmentation and a best positioning compared to conventional product. Tunisian marketers must focus on the factors influencing the behaviour of the Tunisian consumer. They should raise consumer awareness through a suitable communication.

This paper is added to studies of consumer behaviour towards bio-products in emerging countries. The results could serve as a guideline for organizations for understanding the factors and green strategy adopted. This one need to ensure a good segmentation and positioning of biological products compared to conventional product.

Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the wheat production season in India. This study aims to examine whether farmers learn from their past experiences of exposure to climate extremes and use the knowledge to better adapt to future climate extremes.

The authors used data collected from 184 farmers from Haryana over three consecutive wheat seasons from 2013-2014 to 2015-2016 and multivariate logit model to analyse the driver of the adoption of CAW as an ex ante climate risk mitigating strategies based on their learning and censored Tobit model to analyse the intensity of adoption of CAW as an ex ante climate risk mitigation strategy. Farmer’s knowledge and key barriers to the adoption of CAW were determined through focus group discussions.

The analysis shows that the majority of farmers who had applied CAW in the year 2014-2015 (a year with untimely excess rainfall during the wheat season) have continued to practice CAW and have increased the proportion of land area allocated to it. Many farmers shifted from CTW to CAW in 2015-2016.

While farmers now consider CAW as an ex ante measure to climate risks, a technology knowledge gap exists, which limits its adoption. Therefore, designing appropriate methods to communicate scientific evidence is crucial.

This paper uses three years panel data from 184 farm households in Haryana, India, together with focus groups discussions with farmers and interviews with key informants to assess if farmers learn adaptation to climate change from past climate extremes.