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Green building (GB) is an important aspect of sustainable development that advocates for practices that enhance the health and well-being of the occupants and communities with minimal impact on the environment. The adoption of the GB concept is low in most developing countries. This study aimed at assessing the extent of the adoption of GB concepts in Kakamega municipality as a case study. The study sampled 64 respondents which consisted of 15 professionals in the building industry and 49 commercial and residential buildings within the municipality. The results indicated that at least 80% of the professionals were aware of GB concepts of water efficiency, energy efficiency, sustainable materials, sustainable site practices, and indoor environmental quality (IEQ). Water efficiency practices that were widely adopted in commercial and residential buildings were rainwater harvesting and the use of efficient plumbing fixtures. The energy-saving measures adopted were switching off appliances when not in use, use of energy-saving bulbs, and solar energy. The majority of the respondents felt that the indoor air quality was fair. Resource reuse was not widely adopted which could be attributed to a lack of policy or legislation. Low impact development (LID) design of vegetated storm conveyance and rain gardens (bioretention and porous/permeable pavements) was adopted in 42.9% of the buildings. Research into the use of sustainable materials is recommended for wider application as a GB concept. The study recommends the promotion of GB through incentives to enable wider adoption among the owners and developers. Furthermore, GB legislation and certification programs need to be adopted in Kenya. This study was largely based on Leadership in Energy and Environmental Design (LEED) criteria and thus further studies are required on other assessment tools and methods.

While the Olympic Games are always under the spotlight, the Paralympic Games are somehow ignored. This paper aims to invite the general public to think about the para-athletes and the differential treatments they received.

Among the participating countries, many of them were unable to win a single Olympic or Paralympic medal. When the dependent variable is left-censored, ordinary least squares regression is asymptotically biased downwards. In the literature, researchers typically employ the maximum likelihood Tobit model to take care of the censoring problem. However, some researchers argue that the Hurdle model has an advantage over the Tobit model in identifying the determinants of winning Olympic medals. Following their wisdom, this paper employs both the Tobit and Hurdle models in analysis.

The empirical evidence gathered in this paper suggests that population size, host status and average years of schooling are the big three socio-economic determinants when it comes to winning medals at the Paralympic Games and Olympic Games. The findings support the hypothesis that sports talent is randomly distributed and a large country has a higher chance to have talented athletes or para-athletes winning the Olympic medals. The strong host advantage also showed up in the following Paralympics but was not so strong at the next Olympics.

This paper not only examines the relationship between various social, economic and political factors in determining the success of a nation in the Paralympic Games but also attempts to identify possible non-traditional determinants.

Entrepreneurship can help tackle economic problems, such as unemployment. It is often promoted through education programs. There is a limited comprehensive and rigorous understanding of how entrepreneurship education programs and their ubiquitous distance delivery affect young people's entrepreneurial self-efficacy and intention, particularly in non-formal settings. The purpose of this study is to address this gap.

Underpinned by the Social Cognitive Theory, this paper investigates the effects of one entrepreneurship education program in a study with 145 young people from five countries aged 18 to 25 years, 62 Intervention and 83 Control participants. The program's impact on the participants' entrepreneurial intention and self-efficacy (across six sub-dimensions) was assessed in a one-off two-week quasi-experiment. Ex-ante and ex-post self-reported data were collected about the participants.

One-way analyses of covariance were performed to assess separately for changes in the Intervention participants' answers, relative to the Control group. The results of this study suggest the program significantly affected all measures.

These findings contribute to the discussions on the education programs’ effectiveness in promoting entrepreneurship. As a result, they may contribute to entrepreneurship education overcoming geographical and socio-economic hurdles (cost, time and entry barriers) to advance the development of industry, economy and community worldwide.

The objective of this chapter is to discuss how different techniques in Regional Science and Peace Science and the emerging techniques in Management Science can be used in analysing Disaster Management and Global pandemic with special reference to developing countries. It is necessary for me to first discuss the subjects of Disaster Management, Regional Science, Peace Science and Management Science. The objective of this chapter is to emphasise that the studies of Disaster Management should be more integrated with socioeconomic and geographical factors. The greatest disaster facing the world is the possibility of war, particularly nuclear war, and the preparation of the means of destruction through military spending.

The aim of this paper is to use the special context of the Kenyan encampment policy to interrogate the role of social capital as a driver of resourcing for entrepreneurial action in the resource-constrained environment of refugee entrepreneurship in Kenya.

This paper takes conceptual and case study approaches to investigate how refugees deploy social capital to aggregate and recombine resources for entrepreneurial action and livelihood outcomes. It draws on 21 selected secondary sources and semi-structured interviews of 24 respondents from Kakuma camp and Kalobeyei settlement, as well as Nairobi city in Kenya.

This study proposes a new conceptual framework that illuminates the interaction between social capital, resource aggregation and resource recombination for entrepreneurial action and livelihood recovery. This framework was elucidated within the specific Kenyan context, where social capital was found to play a key role in enabling access to other resources such as financial and human capital to refugee entrepreneurs that would otherwise be inaccessible within the resource-constrained context. It also underlines the capacity of refugees to mobilise these resources in the creation of new ecosystems and institutions.

While the conceptual contribution of the paper holds broad explanatory powers, the empirical aspect is limited in terms of its focus on the Kenyan contexts. Future studies can benefit from cross-country comparisons of empirical, including longitudinal, data.

This paper argues for a new approach that can enable better integration of refugees through the provision of opportunities for full economic participation for refugees. This will be a win-win outcome for both refugees and host communities.

This paper makes original contribution by proposing a new conceptual framework that explains the bricoleur’s resource process through the lense of social capital in a resource-constrained and challenging institutional environment. This framework is elucidated with empirical qualitative data from Kenya. This study also signposts new operational and policy directions for humanitarian action among refugees.

The purpose of the study is to investigate micro determinants for dynamic wine pricing in Argentina. We test whether attributes and time affect the price rate of change. The rate of change is selected given the inflationary context of the country. The analysis provides valuable information for wine marketing decisions.

The modeling approach relies on panel data analysis for exploiting the data cross-section and time dimension. The contribution explores a massive price dataset at a weekly frequency. The dependent variable is the weekly price variation rate for product/wine and covariates are attributes, time and nominal variables. Given that endogeneity issues arose, the estimations rely on a two-stage least squares and instrumental variables with cluster-robust errors.

Estimations show that attributes, time and cost variables are statistically significant, with clear seasonal patterns and quality segmentation affecting pricing: wines made out of specific grapes such as Chenin, Merlot and Seedling or composing a broad category such as red wine, exhibit price undershooting (price rate of change below average). On the other hand, wines out of grapes such as Bonarda, Margaux, Mistela, Moscatel, Oporto, Tannat and Sauvignon Blanc show price overshooting (rate of change above average). In summary, wine made from determined grapes and specific wineries show divergent pricing.

Covariates such as alcohol content, label descriptor information, winery history, substitute competition and vintage, among others, have not been considered given that the research analyzes more than 750 wine products. Another limitation is that the work does not explore many time-series covariates, such as promotions and idiosyncratic shocks.

The contribution presents new information on wine pricing patterns affected by weeks, months and years, including the effect of the prolonged 2020 Argentine lockdown. It also analyzes estimations on pricing at the level of grape/blend and wineries previously unknown in this market. The information can influence inventory decisions on the side of the sellers and purchase decisions on the side of consumers.

The analysis includes fine but also low-cost wines that form part of the diet of low-income families in the country. The work detects a divergent pattern in pricing divided by the quality/price of the wine. It also presents information on price timing that may help consumers in the best moment to buy.

The contribution analyzes unprecedented information on weekly wine prices and presents evidence of pricing tactics from a point-of-sale perspective: It identifies different adjustment speeds related to product features and time effects.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.