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Human resource (HR) process research emerged as a response to questions about how (bundles of) HR practices related to organizational outcomes. The goal of HR process research is to explain variability in employee and organization outcomes by focusing on how HR practices are intended (adopted) by senior managers, the way that these HR practices are implemented and communicated by line managers, and how employees perceive, understand, and attribute these HR practices. In the first part of this chapter, we present a review of 20 years of HR process research from the start, to how it developed, and is now maturing. Within the body of HR process research, several different research theoretical streams have emerged, which are largely studied in isolation without benefiting from each other. Therefore, in the second part of this chapter, we draw on previous work to propose a staged process model in which we integrate the different research streams of HR process research, recognizing contingencies in the model. This leads us to an agenda for future research and practical implications in the final part of the chapter.

Higher education has begun to attend to the importance of collaboration and self-awareness for educating sustainability leaders. However, there has been limited discussion on how to design a pedagogy that supports the development of these competencies, particularly the development of self-awareness. In this chapter, we introduce an experiential pedagogy in which students and faculty work together to develop self-awareness as the basis for sustainability leadership. We present three pedagogical principles that support the emotional learning that is foundational for sustainability leadership: student self-discovery, faculty as co-learners, and a developmentally focused learning environment. We demonstrate how these three principles work together to enable students and faculty to grow their self-awareness, providing the foundation for sustainable leadership. We conclude with a discussion on how management educators can learn from this case to develop sustainability leaders who have the self-awareness and relational competency to lead positive, inclusive organizations that are committed to sustainable business practices.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

Schools exist because of the children they educate but examples of their voice influencing their education in an authentic manner can be rare. This chapter outlines the importance of pupil voice and defines the key aspects of authenticity. It uses the themes emanating from this definition as examples of establishing practices to support pupil voice in the classroom. Such practices are based upon the findings of a pupil voice study into the experiences of 14–16-year-old children in physical education (PE) lessons. This PE project was driven by the pupils and adult voice was militated in order to enhance the authenticity of the findings. The project empowered children to raise and discuss the issues they deemed important and find their own solutions without steering or influence by their teachers. The implementation of these findings in one school demonstrated the dynamism and potential of learning based upon child-centred practice.

The research on the positive effects of children’s learning in and with nature is persuasive yet a deeper examination of the contemporary and historical discourses suggests that the school garden has been neither welcoming nor accessible to all children. Its detrimental effects on groups of children have been masked within the discourses of urban children’s health and wellbeing, environmental stewardship, and children’s connection with nature. The school garden has been used historically to enact adult agendas to contain and protect urban children from the social ills of modernity; civilise and assimilate marginalised, impoverished, and immigrant groups; and make future industrial and agricultural labourers who would in turn, entrench the white affluent society’s economic and social positions. In this sense, the school garden was used to reinforce patriarchal, colonial, white supremacist, and eugenic aspirations. We consider the school garden movement in North America through a discourse analysis of historical school garden texts to explore how childhoods were culturally constructed and how these discourses have influenced children both in the past and present.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

This paper aims to offer a new history of management by tracing a religious dimension of scientific management. The thesis is that the good was foundational for bringing scientific management to success in Taylor’s native Quaker Philadelphia in the 1880s. The paper’s main contribution is to contrast the philosophical origins of Taylor’s ideas in scientific management to his native Quaker roots, and how Taylor, over time, into the 1910s, wrestled with this issue.

The paper is situated in historical interpretivism and subjectivism, leaning on contextual and narrative research on religious morality.

Quaker morality prevented managerial opportunism at Taylor’s Midvale Steel in the 1880s. Conversely, by the 1900s and 1910s, interest conflicts between workers and managers escalated when scientific management moved out of its traditional cultural contexts of Quaker Philadelphia and spread across the USA. The historical implication is, already for Taylor’s time, that scientific management never was the “one-best way” of management.

Future research needs to deepen and broaden research on scientific management when tracing the significance of religion and culture in management thought.

The paper has implications for modern studies of business morality by uncovering the practical relevance of religious business ethics at the outset of management studies.

The historic emergence of scientific management points to a theory of institutional evolution and economic growth, when religiously grounded governance of the firm deinstitutionalized, and institutional economic governance, with different but superior economic advantages, progressed by the 1900s.

The paper suggests an alternative version of the intellectual heritage of management studies by tracing the legacy of Taylor’s Quakerism and how religious and cultural ideas contributed to the formation of science in management.