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Marginalization of women in STEM sectors is a widely discussed trend that has percolated into the corporate sector. The purpose of this study is to identify factors that act as barriers to entry to female entrepreneurs and to understand the impact of these factors in the context of startup landscape. The scope of this paper covers chiefly first-generation entrepreneurs while elaborating the presence of the Lucite ceiling effect. It aims to categorize and elucidate the responsible variables while developing a model for the same.

The research is an exploratory study that provides a complex picture of how female entrepreneurs understand and experience the work culture at their workplace. The population under consideration is “urban startups”; these have been characterized as technology/non-technology-based and non-agricultural in nature. The sample in the study consists of male and female entrepreneurs of first-generation entrepreneurs belonging to the urban middle class and either founders or co-founders. The exploration presents a groundbreaking examination based on narrative inquiry and semi-structured interviews.

The research led to distinct findings that can be utilized to improve the condition of female entrepreneurs and encourage their involvement in the ecosystem. The model is proposed on the basis of extrinsic and intrinsic factors, which lead to the Lucite ceiling phenomenon. The causes ranging from family pressure to fulfilling relevant requirements such as financing the venture were classified under these. Ultimately, inferences were drawn as to how these may be affecting the growth of women in the sectors.

The identified intrinsic and extrinsic factors have been detailed, presenting further opportunities to focus on specific metrics by the stakeholders, namely, the policy-makers and the entrepreneur community. The study has been limited to urban startups to allow for convenience sampling, which is justified considering the issues highlighted in the existing knowledge. While this study has been carried out in the context of urban startups, it leaves scope for extension and extrapolation of the presented model in the rural context.

The study presents a formally structured representation of the issues faced by female entrepreneurs in a manner which is mutually exclusive and collectively exhaustive. Such a categorization can, in the contemporary times, enable targeted mitigation of the same through well-planned policy initiatives and legislation. In addition, it provides a strong baseline for extensive quantitative research in this field, especially in the context of emerging economies in fast-developing nations.

The framework helps lay a groundwork for thoughtful research on women’s entrepreneurship. The Lucite ceiling phenomenon is a more aggravated version of the “glass ceiling”. The reasons for the prevalence of this effect in this context have not been explored before, thus providing a great scope to be further investigated.

Accelerated life test is undertaken to induce early failure in high-reliability products likely to last for several years. Most of these products are exposed to several fatal risk factors and fail due to one of them. Examples include solar lighting device with two failure modes: capacitor failure, and controller failure. It is necessary to assess each risk factor in the presence of other risk factors as each one cannot be studied in isolation. The purpose of this paper is to explore formulation of optimum time-censored accelerated life test model under modified ramp-stress loading when different failure causes have independent exponential life distributions.

The modified ramp-stress uses one test chamber in place of the various chambers used in the normal ramp-stress accelerate life test thus saving experimental cost. The stress-life relationship is modeled by inverse power law, and for each failure cause, a cumulative exposure model is assumed. The method of maximum likelihood is used for estimating design parameters. The optimal plan consists in finding out relevant experimental variables, namely, stress rate and stress rate change point(s).

The optimal plan is devised using D-optimality criterion which consists in finding out optimal stress rate and optimal stress rate change point by maximizing logarithm of determinant of Fisher information matrix to the base 10. This criterion is motivated by the fact that the volume of joint confidence region of model parameters is inversely proportional to square root of determinant of Fisher information matrix. The results of sensitivity analysis show that the plan is robust to small deviations from the true values of baseline parameters.

The model formulated can help reliability engineers obtain reliability estimates quickly of high-reliability products that are likely to last for several years.

The purpose of this paper is to assess Indian consumers' brand consciousness by examining their brand knowledge, purchase behaviour and perceptions of foreign brands. It provides key inputs for global retailers to harness the potential in growing consumerism in India.

A survey of 300 Indian consumers was conducted and the data were analysed using descriptive and simple regression techniques.

The study found that brand purchase in India varies across product categories. At present, consumer knowledge and use of foreign brands is low, and Indian consumers are price‐sensitive. Indian consumers are experimenting with brands and would like more foreign brands to enter the Indian market.

Due to the small sample size, advanced econometrics techniques could not be used to analyse the dataset.

The paper is the first to assess the impact of retail liberalisation on Indian consumers' shopping behaviour, particularly their brand consciousness.

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.

This study aims to analyze the perceptions of smallholder farmers on climate change and events and further explores climate change adaptation strategies and associated challenges. The findings provide useful information for enhancing the adaptive capacity of smallholder farmers to adjust to climate-related hazards and improve their resilience and disaster preparedness in northern Ghana.

This study uses a multistage sampling procedure and sample size of 150 farmers, the Binary Probit Model (BPM), to identify and examine the determinants of climate change adaptation strategies adopted by smallholder farmers. Also, the constraints of adaptation were analyzed using Kendall’s coefficient of concordance.

The results from the BPM and statistics of Kendall’s coefficient revealed that the farm risk level, ability to adapt, farmer’s income, age, farming experience, climate change awareness and extension visits were factors that significantly influenced the adaptation strategies of smallholder farmers (in order of importance). The majority (60%) of the farmers ranked farm risk level as the major constraint to adopting climate change strategies.

The findings of this study enhance understanding on access to relevant and timely climate change adaptation information such as an early warning to farmers during the start of the farming/rainy season to support their adaptive responses to climate change.