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This paper examines the impact of lived experiences and attitudinal blueprints on researchers within the context of masculinities research. It explores the negotiation of gendered roles, exploring how personal narratives shape our engagement in gender research and the collaborative process of meaning-making. It discusses the methodological tensions surrounding narrative research and naturalistic inquiry when investigating masculinities.

Adopting a feminist post-structuralist lens, this paper analyses the discursive nature of masculinities and its theoretical and historical construction, alongside the use of narrative research methodologies in research practices.

The paper reinforces the importance of feminist frameworks in deconstructing gender norms and challenging implicit assumptions. The role of reflexivity in the research process and the potential for researcher subjectivity as a resource is emphasised. Drawing on existing scholarship and the authors' empirical research experiences, the importance of researcher reflexivity in recognising the potential for gender performativity in the research setting is emphasised, especially in gendered research spaces and when engaging with methodologies tacitly understood through gendered ideological lenses.

The paper contributes to ongoing scholarly discussions exploring the intersection of gender, theory and practice.

The paper's theoretical exploration contributes to understandings of gender dynamics in research and offers insights into the complexities of conducting masculinities research from a critical perspective. The paper contributes to ongoing scholarly discussions exploring the intersection of gender, theory and practice.

This chapter examines two 21st-century Disney fairy tale adaptations, Frozen (2013) and its sequel Frozen II (2019), focussing on the representation of male characters and the discourse on masculinity that can be inferred from both films.

Despite featuring two prominent female protagonists – Queen Elsa and Princess Anna – and dealing with themes such as sisterhood and female bonding, a close reading of the two films reveals that they are as much about masculinity as they are about femininity. For instance, filmmakers introduce heterosexual romance where there was none before, as well as male characters Prince Hans and Kristoff, who are not present in the literary source that they draw from, Hans Christian Andersen's ‘The Snow Queen’ (1844).

Furthermore, these male characters are given names, personalities, and motivations, which cannot be said of previous Disney fairy tale Prince Charming-type figures. Therefore, Hans and Kristoff are proposed to be variations of this archetype and can be read as an attempt on Disney's part to complicate it, undermine the patriarchal masculinity that it stood for in its previous Disney renderings, and propose alternative models for the implied 21st-century audience.

Although Prince Hans is initially presented as a stereotypical Disney fairy tale prince, he is eventually revealed to be a narcissistic lover and a patriarchal villain. Kristoff, by contrast, is the humble, lower-class, sensitive ‘new’ man who is presented as a socially acceptable alternative and finally takes Prince Charming's place by becoming the princess's love interest and partner. Frozen can be read as a cautionary tale that urges young women to choose their romantic (male) partners wisely and warns both male and female audiences against the dangers of fragile patriarchal masculinity.

Although special education was built upon the foundation of the Civil Rights Act of 1964, the discrimination that many racialized students receiving special education services experience cannot be denied. Many culturally, ethnically, and linguistically diverse students receiving special education services encounter labels that perpetuate racism and ableism and lead to inequitable access to services and resources necessary for more positive postsecondary outcomes. By honoring intersectionality and dismantling the singular identity, educators can become change agents and shift the historic oppressive narrative to create a system of empowerment as these individuals transition from transitional kindergarten to age 21 special education programs (TK-21) schools into adulthood.

This study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.

Three operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.

The obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.

The value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

The current research aims to map and investigate how human resource management and lean practices can be integrated. This investigation will help identify the HRM aspects critical in the success of lean initiatives while exploring the research gaps in the existing literature. The review also aims to delineate the benefits and challenges of integrating lean with HRM systems to discuss further research and practice areas.

This study utilizes a systematic literature review method to identify and synthesize the existing literature. As part of the process, a protocol that provided a plan for the review was followed, including the research questions and the data to be extracted.

The study results indicate that aspects of HRM practice and policies such as training and development, teamwork, motivation, communication, leadership, are key enablers of lean initiative deployment and success. The benefits of the integration of human resources with lean can help in lean training and development, communication of lean initiatives and successes, allocating and hiring continuous improvement personnel, and supporting leadership in lean deployment. Challenges to integrating lean and HRM practices included lack of integration and collaboration between disciplines. Further exploration areas in successful lean deployment would be practical longitudinal case studies on lean deployments with human resource (HR) partnerships and involvement.

This review paper has crucial implications for practice relating to, integration of lean with HRM structures and tailoring HRM initiatives to ensure the success of lean deployment and reduce risks of failure.

The systematic literature review study conducted in this paper is the first of its kind to integrate and map the HRM concepts that can be integrated with Lean to deploy the initiative successfully. This mapping is critical for ensuring the success of lean methodologies within an organization and paves the way for future research. In addition, managers and organizations can find support and guidance from this study to focus on vital areas of partnership between their lean and HR programs.

This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.

The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.

The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).

As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.

The number of disabled students participating in higher education (HE) and availing support services has increased 268% from the years of 2008/2009 to 2021. Disabled students face a range of transitional barriers that their non-disabled peers do not, including ableist attitudes, and inaccessible environments. The PhD research upon which this chapter is based investigated the social engagement experiences of disabled students in HE. It examined qualitative data from 65 participants, with representatives from 19 HE institutions (HEIs) across Ireland using a four-phased, sequential and concurrent qualitative data collection methodology. This chapter will focus on one phase of this PhD research design, namely phase one, which captured the voice of disabled undergraduate students (n = 23). The research identified that disabled students value social engagement, but barriers impact upon students' social engagement, having their voice heard, their ability to form connections, affecting students' sense of belonging. Based on my PhD findings and my work to implement them, I would argue that ‘consultation’ with disabled students is currently taking place in its most basic form. HE needs to embrace the disruptive potential of disabled people and move from passive to active listening, from meaningless consultation to meaningful consultation and then to collaboration and partnership.