Search results

The context of sustainable development dwells, quite significantly, upon the one of gender parity in a society and nation. This is so because the issue of gender equality is key to distributive justice, which is in turn much essential for creating a good amount of precondition for sustainable development. Academic inquests into the problem into the gender disparity are indicative of how gender disparity on economic and social parameter triggers a negative productivity change over time and space. Thus, the current chapter brings forth an analytical approach to contemplating into the above-mentioned narratives in both theoretical and empirical terms. The tack of our analysis is as follows. To begin with, this chapter develops an index to determine the extent of gender disparity in health, education and participation in workforce (namely, Gender Gap Index or GGI). Moving on, the study extends to looking at India changing dynamics on gender gap vis-à-vis developing and less-developed countries. Besides, a general equilibrium model has been developed to unfurl the fallout of gender disparity in terms of the wage gap between male and female workers in the labour force, extant and conditioned further by demographic and sociopolitical factors.

The purpose of this study is to examine relevant demographic and socio-economic factors as they relate to progress towards intercultural communicative competence (ICC) and intercultural sensitivity for ethnic-minority Latinx middle school English learners (ELs) using a mobile-assisted funds-of-knowledge-featured writing practice.

Through the theoretical lens of funds of knowledge, this three-year study implemented a survey-based quasi-experimental design centered on the Latinx ELs’ ICC development with the implementation of an intercultural sensitivity questionnaire (Chen and Starosta, 2000). The authors first investigated the relationship between ELs’ intercultural sensitivity and associated demographic and socio-economic factors. The authors then examined the changes of ELs’ intercultural sensitivity. Over ten weeks, the intervention group completed five funds-of-knowledge-featured narrative essays using pen and paper and mobile-based writing tools alternatively.

Findings indicated that ELs’ intercultural sensitivity increased as they advanced to a higher-level grade from sixth to eighth. The embedded mobile-assisted funds-of-knowledge writing practice as intervention promoted ELs’ intercultural sensitivity in interaction engagement, respect of cultural differences, interaction enjoyment and interaction attentiveness. Among the variables, interaction enjoyment was portrayed the most. ELs who reported not speaking English at home were statistically significant in this experiment.

This study acknowledges the robust and variance of funds of knowledge as a niche to address the interculturality and hybridity of ELs’ cultural practices accumulated through Latinx ELs’ family socialization and social development using mobile-assisted writing practice. This study could provide implications for optimizing inclusive experience to promote computer-assisted language learning in a contemporary, postcolonial global world.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Corruption perception is essential to study because it can shape people’s attitudes toward the government. Thus, the purpose of this paper is to address this key question: what factors are associated with a non-expert’s judgment of whether Canada is corrupt?

This study uses the World Value Survey conducted in Canada in October 2020. This survey is based on a nationally representative sample of a cross-section of adult Canadian residents, including Canadian citizens and permanent residents and those who are neither Canadian citizens nor permanent residents.

Based on this study, some conclusions can be made. First, people accessing corruption news from the traditional news media are less likely than those receiving information from the new media to perceive the state (in this case, Canada) as corrupt. Second, people who have less confidence in public institutions are more likely to perceive a country as corrupt. Third, people who participate in electoral and non-electoral forms of political participation are more likely to perceive the state and its public officials as corrupt. Fourth, regardless of which political party is in power, individuals who lean right politically are more likely than those on the left to perceive the state as corrupt. Finally, immigrants are less likely than those born in Canada to perceive the state as corrupt. This work enriches the literature on the substantive understanding of the factors associated with corruption perception.

Studies investigating factors associated with public perception of corruption tend to focus on developing countries. The current study contributes to filling this gap in knowledge by examining correlates of corruption perception in Canada. As a result, this study contributes to the literature on factors associated with corruption perception, especially in the developed country context.

This empirical research intends to examine factors influencing the adoption of renewable energy (RE) using a conceptual model of the consumer decision-making process.

This study uses a primary response-based survey to collect data from 668 respondents interested in adopting RE for their daily usage. The sample respondents were chosen through a multi-stage random stratified technique. The responses were analyzed through structural equation-based modeling techniques to discuss the findings and suggest further implications.

The findings suggest that factors like knowledge, policy incentives, sustainable development goals (SDGs-7, 11 and 13), socio-economic benefits and risk perception significantly impact the adoption of RE. Besides, risk perception mediates between environmental concerns and the adoption of RE. Also, age has a significant role in RE adoption.

The study finds the critical role of government in introducing financial incentives to reduce the initial cost of renewable adoption. Doing so will also promote clean and equitable energy access to society leading to further fulfillment of SDGs. Additionally, steps like knowledge enrichment, designing suitable policies for a manufacturer and public-friendly renewable market development will further facilitate renewable adoption in society.

With an objective to study the public perception and attitude towards renewable adoption, this empirical research is the first of its kind to carry out a real-time survey of the Indian population and suggest policy implications which would benefit all the concerned stakeholders.

This study aims to understand client food preferences and how pantry offerings can be optimized by those preferences.

This study develops and administers customized surveys to study three food pantries within the Second Harvest Food Bank of Northwestern North Carolina network. This study then categorizes food items by client preferences, identifies the key predictors of those preferences and obtains preference scores by fitting the data to a predictive model. The preference scores are subsequently used in an optimization model that suggests an ideal mix of food items to stock based upon client preferences and the item and weight limits imposed by the pantry.

This study found that food pantry clients prefer fresh and frozen foods over shelf-friendly options and that gender, age and religion were the primary predictors. The optimization model incorporates these preferences, yielding an optimal stocking strategy for the pantry.

This research is based on a specific food bank network, and therefore, the client preferences may not be generalizable to other food banks. However, the framework and corresponding optimization model is generalizable to other food aid supply chains.

This study provides insights for food pantry managers to make informed decisions about stocking the pantry shelves based on the client’s preferences.

An emerging topic within the humanitarian food aid community is better matching of food availability with food that is desired in a way that minimizes food waste. This is achieved by providing more choice to food pantry users. This work shows how pantries can incorporate client preferences in inventory stocking decisions.

This study contributes to the literature on food pantry operations by providing a novel decision support system for pantry managers to aid in stocking their shelves according to client preferences.

This empirical research aims to provide organisations with useful information on how teleworking has affected employee commuting, allowing organisations to adapt working conditions to the new social context. This research sets out to provide evidence on the behaviour of teleworkers in terms of the mode of transport chosen when commuting to work physically.

This research is based on a survey conducted in Madrid based on a theoretical approach grounded in the theory of planned behaviour (TPB) and discrete choice models. Exploratory factor analysis (EFA) and discriminant analysis have been used to determine the variables that influence the mode of transport chosen by teleworkers when commuting in person.

The results indicate the prevalence of private car use by teleworkers when working at the office, finding that attitudes and satisfaction with modes of transport significantly influence their choice. The characteristics and frequency of teleworking, however, are not significant, which indicates that teleworkers attach greater importance to their preferred mode of transport, regardless of the disadvantages.

This research provides empirical evidence using an inductive approach to understand the challenges that organisations are facing with regard to teleworking since commuting behaviour has changed for teleworkers. This requires organisations to give significant reconsideration to the issue of commuting as an important component of working time that could condition employee satisfaction and, therefore, the retention or recruitment of talent. Furthermore, residence and mobility changes afford organisations better access for recruitment, notwithstanding urban planning implications.

The existing literature offers various perspectives on integrating cryptocurrencies into investment portfolios; yet, there is a gap in understanding the behaviours, attitudes and cross-investment links of individual investors. This study, grounded in the modern portfolio theory and the random walk theory, aims to add empirical insights that are specific to the UK context. It explores four hypotheses related to the influence of socio-demographics, digital adoption, cross-investment behaviours and financial attitudes on cryptocurrency owners.

This study uses a logistic regression model with secondary data from the Financial Lives Survey 2020 to assess the factors impacting cryptocurrency ownership. A total of 29 variables are used, categorized into four groups aligned with the hypotheses. Additionally, hierarchical clustering analysis was conducted to further explore the cross-investment links.

The study reveals a significant lack of diversification among UK cryptocurrency investors, a pronounced inclination towards high-risk investments such as peer-to-peer lending and crowdfunding, and parallels with gambling behaviours, including financial dissatisfaction and a propensity for risk-taking. It highlights the influence of demographic traits, risk tolerance, technological literacy and emotional attitudes on cryptocurrency investment decisions.

This study provides valuable insights into cryptocurrency regulation and retail investor protection, underscoring the necessity for tailored financial education and a holistic regulatory approach for investment products with comparable risk levels, with the aim of minimizing regulatory arbitrage. It significantly enhances our understanding of the unique dynamics of cryptocurrency investments within the evolving financial landscape.

This study aims to investigate the determinants of United Arab Emirates (UAE) and Qatar consumers’ perceptions of organic food.

Using a survey approach and focusing on six known determinants identified from empirical studies, data were analysed using a mean difference analysis and a multi-regression model.

Citizens in both countries had similar access to organic food products, yet consumer perceptions differed significantly. Given the geographical, cultural and topographical proximity and similarities of these countries, differences in the mean values indicate that targeted or bespoke marketing is required to attract customers.

One limitation of this study its sample size that may limit the generalizability of its results. However, the highly statistically significant results offset this to some extent as the differences the authors have demonstrated are likely to be real. These do require confirmation by further similar studies. The study relied on a random sample of respondents who might have exhibited bias in answering questions.

The two countries central to this research study, the UAE and Qatar, have vested interests in supporting the organic food product market that mainly concern supporting and promoting the health of their citizens and the environment. As shown in this paper, the key obstacles preventing consumers’ accessing organic products are availability and price. With appropriate governmental subsidies and logistics support, however, these barriers can be overcome.

If governments are sincere in their declarations that the health and welfare of their citizens is of prime importance, they will support attempts to promote the sale and consumption of organically grown food. The results of this study can help to inform such policies.

This study provides insights into the most important factors that influence consumers’ attitudes towards organic foods. This study fills a gap in the existing research on consumer buying behaviour for organic food in two Middle Eastern countries.

This study aims to examine the perception and practices related to Corporate Social Responsibility (CSR) implemented in Small and Medium-sized Enterprises (SMEs), focussing on small hotels in London.

A qualitative research design comprising detailed semi-structured interviews was employed with 12 small hotel owner-managers in central London and its outskirts. The study adopts a social constructionist approach to explore CSR perspectives and practices, along with a social capital framework to investigate how CSR is perceived at the individual level and consequently manifested into CSR practices.

The findings indicate that a small hotel’s implementation of CSR is influenced by long-term versus short-term considerations, as well as socio-economic and socio-political conditions. Individual-level factors, like hoteliers’ CSR conceptualisation and personal and business values, affect CSR adoption in small hotels. Lastly, institutional-level factors, such as ineffective institutional participation and the hotelier’s cultural background against the cosmopolitan context of a big city, have contributed to a muted response to socially responsible issues.

This study was conducted with a limited sample of 12 participants from small hotels in London and its outskirts, which may limit the generalisability of the findings. Future research could enhance these findings by involving a larger and more diverse group of participants from various urban areas, potentially employing a quantitative research approach for broader applicability. This study’s insights can guide policymakers in educating small business owners on CSR benefits and implementation. It also proposes how governments could encourage sustainable practices among small hotels seeking to enhance their reputation. Moreover, these findings enable small businesses to develop their stakeholder strategies for greater CSR initiatives.

This study integrates social capital theory into investigating CSR in small hotels in London, broadening the literature on CSR perception and integration, particularly in SMEs and the hospitality sector.