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Working conditions, pay rates and the rights of workers to collectively negotiate have become important points of discussions in recent years, with support for unions and union applications rising to levels long unseen in America. In many instances, though, companies have responded aggressively. This is not the first time such a dynamic has played out in American business. This study aims to take a fresh look at one of America’s most prominent historical disputes between labor and ownership – the Homestead Massacre of 1892 – to glean lessons from that conflict that remain relevant to today’s business environment.

This study adopts game theory and the principles of repeated interaction to assess how differing discount factors led to differences in time orientations between the workers and the Carnegie company. These differing time orientations affected both the strategy each side deployed in the negotiations and the payoffs received by the parties. Letters, contemporary news reports and histories of the events leading up to and immediately following the 1892 Homestead Massacre are qualitatively analyzed with a genealogical pragmatic approach.

Differences in temporal orientation between management and workers exacerbated the conflict, with the workers adopting a more cooperative stance and distal time orientation, while the Carnegie company negotiated with a proximal time orientation and played to “win” a game that, in fact, could not be fully won or lost given its infinitely repeating nature. The result was a short-term victory for the Carnegie company but with long-term negative consequences that highlight the suboptimal outcome the company achieved by playing a proximal strategy in an infinite game.

Although the incident at Homestead is a well-studied labor dispute, many of the themes that preceded the incident have resurfaced in the modern work context. This work, by adopting game theory as an analytical framework, provides new insights into management mistakes that led to the labor conflict and lessons for what present-day managers can do to avoid exacerbating labor strife.

People donate to charities with the aim of improving society. Yet, many charities fail to use donations efficiently or have ineffective interventions. The authors explore the strategic operational priorities and processes that enable charities to efficiently implement their interventions and have a positive impact on society.

The authors first review the literature on charities to gain a deeper understanding of the current state of knowledge on charity operations. The authors then employ the lens of paradox theory and perform a qualitative investigation of six case studies to explore various aspects of the operations of charities that are known for being cost-effective.

The authors reveal how the strategic operational decisions of charities, as well as the processes they implement, help them resolve the tensions arising from the cost-effectiveness paradox. The authors show that cost-effective charities make strategic operational decisions that help maintain two diverging priorities: prioritizing the status quo and prioritizing change in how they deliver value. Another set of strategic decisions helps balance these two diverging priorities. The authors then show how these charities create and then maintain cost-effective operations.

The authors address recent calls for research on non-profit organizations in the field of operations management. To authors’ knowledge, it is the first in-depth study of exemplary charity operations. The results can be used by charity executives as a benchmarking tool when they develop and implement their charitable interventions and by government agencies and potential donors when they select charities for their donations. Finally, the results should have implications for other organizations trying to have a positive societal impact.

Access to clean drinking water is a major encumbrance in developing countries. In Ghana, urban water supply is below internationally recognised standards, especially among the urban poor, sub-urban and rural communities. Stakeholders and institutional inefficiencies may be hindrances facing the Ghanaian water supply process. Therefore, this study aims to appraise the motivational factors and outcome of stakeholders’ engagement and identify the factors that influence effective institutional management of urban water supply in Ghana.

Sequential exploratory mixed methods were adopted and analysed to proffer answers to the research questions. Nineteen participants and 521 respondents were sampled for the qualitative and quantitative phases.

Findings reveal that the institutional processes and stakeholder engagement significantly influence the effectiveness of the management of urban water supply in Ghana. Findings identified 35 motivational factors and categorised them into the health of the population, socio-economic, technological and innovation trends, policy reform and adaptive governance. Also, the 22 institutional factors identified were categorised into three groups: regulatory framework, ethics for managing water supply and the culture of managing water supply.

Besides the study addressing the theoretical gap regarding which variables are germane in influencing the effective management of urban water supply, the study may be among the top studies that have appraised the role of stakeholders in the institutional management of urban water supply in Ghana.

Errors are increasingly recognized as beneficial to the learning process and are more frequently integrated into training curriculums. Despite this growing interest, the work carried out so far offers little evidence highlighting the psychological qualities implicit in learning from error. By focussing on the role of specific trainee’s attributes [i.e. learning goal orientation (LGO) motivation to learn and metacognition], this study aims to better understand the reasons why some trainees benefit more (than others) from being confronted with errors during training.

A total of 142 trainees took part in this study by participating in a training on interviewing techniques that also exposed them to various committable errors, and by completing questionnaires at two different times (i.e. before and after training).

Results of bootstrap regression analysis highlights three main findings: LGO is positively linked to learning from errors; a significant portion of the link between LGO and learning from error is explained by motivation to learn and metacognition; and these effects are presented in the form of a double-mediated model which suggests two different explanatory pathways (i.e. motivational and cognitive).

To the best of the authors’ knowledge, this study is among the first to offer insight on the psychological attributes influencing learning from errors and to bring forward the role of two underlying mechanism that are linked to this specific type of learning. It also invites researchers and practitioners to reflect on the best ways to make use of errors in training and promote the value of personal attributes on trainees’ learning experience.

The primary aim of this paper is to concurrently use the data types to enhance econometric analysis in the housing market in developing countries, particularly Namibia.

Scholarly discussions on econometric analysis in the housing market in sub-Saharan Africa suggest that the inadequacy of time series data has impeded studies of such nature in the region. Hence, this paper aims to comparatively analyse the impact of economic fundamentals on house prices in Namibia using real and interpolated data from 1990 to 2021 supported by the ARDL model.

It was discovered that in all the three types of data house prices were affected by fundamentals except real GDP in the long term. It was also noted that there were not much significant variations between the real data and the interpolated data frequencies. However, the results of the annual data and the semi-annual interpolated data were more analogously comparable to the quarterly interpolated data

It is suggested that the adoption of interpolated data frequency type should be based on the statistical significance of the result. In addition, the need to monitor the nexus of the housing market and fundamentals is necessary for stable and sustainable housing market for enhanced policy direction and prudent property investment decision.

The study pioneer to concurrently use the data types to enhance econometric analysis in the housing market in developing countries.

The purpose of this review paper is to provide a review of the most recent advances in the field of manufacturing composite sandwich panels along with their advantages and limitations. The other purpose of this paper is to familiarize the researchers with the available developments in manufacturing sandwich structures.

The most recent research articles in the field of manufacturing various composite sandwich structures were reviewed. The review process started by categorizing the available sandwich manufacturing techniques into nine main categories according to the method of production and the equipment used. The review is followed by outlining some automatic production concepts toward composite sandwich automated manufacturing. A brief summary of the sandwich manufacturing techniques is given at the end of this article, with recommendations for future work.

It has been found that several composite sandwich manufacturing techniques were proposed in the literature. The diversity of the manufacturing techniques arises from the variety of the materials as well as the configurations of the final product. Additive manufacturing techniques represent the most recent trend in composite sandwich manufacturing.

This work is valuable for all researchers in the field of composite sandwich structures to keep up with the most recent advancements in this field. Furthermore, this review paper can be considered as a guideline for researchers who are intended to perform further research on composite sandwich structures.

COVID-19 continues to spread, and cause increasing deaths. Physicians diagnose COVID-19 using not only real-time polymerase chain reaction but also the computed tomography (CT) and chest x-ray (CXR) modalities, depending on the stage of infection. However, with so many patients and so few doctors, it has become difficult to keep abreast of the disease. Deep learning models have been developed in order to assist in this respect, and vision transformers are currently state-of-the-art methods, but most techniques currently focus only on one modality (CXR).

This work aims to leverage the benefits of both CT and CXR to improve COVID-19 diagnosis. This paper studies the differences between using convolutional MobileNetV2, ViT DeiT and Swin Transformer models when training from scratch and pretraining on the MedNIST medical dataset rather than the ImageNet dataset of natural images. The comparison is made by reporting six performance metrics, the Scott–Knott Effect Size Difference, Wilcoxon statistical test and the Borda Count method. We also use the Grad-CAM algorithm to study the model's interpretability. Finally, the model's robustness is tested by evaluating it on Gaussian noised images.

Although pretrained MobileNetV2 was the best model in terms of performance, the best model in terms of performance, interpretability, and robustness to noise is the trained from scratch Swin Transformer using the CXR (accuracy = 93.21 per cent) and CT (accuracy = 94.14 per cent) modalities.

Models compared are pretrained on MedNIST and leverage both the CT and CXR modalities.

This paper aims to present a theoretical model for restructuring Colombia’s educational initiatives in response to current socioeconomic needs. More equitable and decolonized education could help learners decouple their capacities to imagine the future from colonialized paradigms, thereby opening spaces for more active engagement in their own futures.

The authors take a critical, postmodern approach focused on empowering people to transcend constraints from a colonial past and recognizing that the purpose of knowledge, although reflecting power and social relationships, is to help people improve society. Notions of situated and futures literacies nourish an approach toward a decolonized and glocalized educational model.

The current Colombian educational system tends to favor a single focus – local, national or international – at the expense of the others. The authors argue that educational policy and planning should account for three realms of knowledge: locally situated literacies, nationally situated literacies and globally situated literacies.

Deconstructing obsolete and colonized methodologies could not only help prepare Colombian learners for active engagement both within and beyond their modern-day borders but could also help transform other educational systems originally designed to support societies and economies that no longer exist, including those of the Global North.

This study aims to asses students’ sustainability consciousness (SC) in relation to their perceived teaching styles in seven public sector institutions in Pakistan.

A survey technique was used to collect data from respondents. Grasha’s (1996) Teaching Styles Inventory and Gericke et al.’s (2019) Sustainability Consciousness Questionnaire were used to collect data pertinent to teachers’ teaching styles and students’ SC, respectively. This study’s population was 1,986 students studying in seven educational institutions. A sample of 993 students was selected for the study. Out of the 993 questionnaires distributed, only 753 respondents returned the questionnaire completely filled, resulting in a response rate of 75.83%. Descriptive statistics and structural equation modeling (SEM) were used to analyze the data.

The results show that students’ mean scores on environmental and social dimensions were higher compared with the economic dimension. Similarly, students’ scores were relatively higher on the knowledge and attitude dimension while lower on the behavior dimension. Moreover, the expert and formal authority teaching styles were the most prevalent teaching styles. Furthermore, SEM results show that various teaching styles affected students’ knowledge and attitude; however, only the delegator teaching style affects all three dimensions of SC.

This research has implications for educational institutions and policymakers to ensure dedicated efforts to promote and integrate education for sustainable development into the educational system and achieve sustainability goals by 2030.

The study findings will help future teachers to effectively integrate sustainability education into their classrooms.

This research expands the discussion on the effectiveness of various teaching styles on SC in teacher education programs.

The mortality rate due to skin cancers has been increasing over the past decades. Early detection and treatment of skin cancers can save lives. However, due to visual resemblance of normal skin and lesion and blurred lesion borders, skin cancer diagnosis has become a challenging task even for skilled dermatologists. Hence, the purpose of this study is to present an image-based automatic approach for multiclass skin lesion classification and compare the performance of various models.

In this paper, the authors have presented a multiclass skin lesion classification approach based on transfer learning of deep convolutional neural network. The following pre-trained models have been used: VGG16, VGG19, ResNet50, ResNet101, ResNet152, Xception, MobileNet and compared their performances on skin cancer classification.

The experiments have been performed on HAM10000 dataset, which contains 10,015 dermoscopic images of seven skin lesion classes. The categorical accuracy of 83.69%, Top2 accuracy of 91.48% and Top3 accuracy of 96.19% has been obtained.

Early detection and treatment of skin cancer can save millions of lives. This work demonstrates that the transfer learning can be an effective way to classify skin cancer images, providing adequate performance with less computational complexity.