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Economies and societies are not digitally isolated. Digital technologies are widely recognised as key drivers of information dissemination, knowledge sharing, income and employment. Digital technologies also influence the interlinkages of digitalisation, gender and labour market outcomes. Digital technologies impact every sphere of day-to-day life. It impacts ways of communication, trade and business; influences networking abilities; shapes societal norms, attitudes and behaviours. It is hence argued that digital technologies may have crucial implications for women's participation in the workforce.

Gender equality and increasing women's workforce participation is an important goal under the United Nations Sustainable Development Goals (SDGs). Research indicates that women are mainly involved in agricultural work, blue-collar formal work, while collar formal work, and entrepreneurship. Digital technologies significantly impact the ways of working in all these sectors. Consequently, it is argued that digital technologies influence women's participation across all such types of work.

This chapter aims at unravelling the linkages between digital technologies and women's workforce participation. To this end, the influences of digital technologies on women's participation in agricultural work, blue-collar formal work, white-collar formal work and entrepreneurship are discussed. The implications and impacts of the use of broadband, internet and mobile technologies are also discussed. This chapter also includes important theories of women's workforce participation and discusses them in light of digitalisation.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

Employing the “Job demands-resources (JD-R)” framework, this study examines the impact of co-occurring social supports (supervisor, coworker, and family support) on the telework environment and employee engagement.

The study uses a multimethod approach. Data from 294 employees belonging to Indian technology organizations were collected and analyzed using the partial least squares (PLS)-based structure equation modeling software SmartPLS4. Following this, necessary condition analysis (NCA) was carried out using the NCA package for R.

Telework environment was found to mediate the relationship between social support and work engagement. Supervisor support and instrumental family support were identified as predictors as well as necessary conditions for telework environment. Coworker support was identified both as a predictor and necessary condition for telework environment. Although emotional family support was found to be a predictor of telework environment, it was not identified as a necessary condition.

The findings indicate that coworker support and family instrumental support are as important for telework success as supervisor support. Moreover, our findings suggest that varying levels of telework environments (low, moderate, and high) may necessitate distinct social support configurations. Consequently, organizations should match their social support configuration to match their overall teleworking strategy.

A basic premise of the JD-R framework is that resources exist in caravans (bundles). However, previous research (in telework) has concentrated on only one or two kinds of social support, that too in varying situational contexts, limiting generalizability of the findings. This has also produced inconsistent conclusions concerning the role of support providers such as coworkers and family. Recent developments in JD-R also suggest that the role of resources may vary in terms of their importance (necessity) for work engagement. By augmenting standard regression-based techniques with NCA, the authors explore these issues to provide a more thorough understanding of the influence of social supports on work engagement in telework situations.