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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.

This paper aims to identify and evaluate resolutions to key learning and teaching challenges in very large courses that involve practical mathematics, such as foundational finance.

A design-based research approach is used across three semesters to iteratively identify practical problems within the course and then develop and evaluate resolutions to these problems. Data are collected from both students and teachers and analysed using a mixed-method approach.

The results indicate that key learning and teaching challenges in large foundational finance courses can be mitigated through appropriate consistency of learning materials; check-your-understanding interactive online content targeting foundational concepts in the early weeks; connection points between students and the coordinator to increase teacher presence; a sustained focus on supporting student achievement within assessments; and signposting relevance of content for the broader program and professional settings. Multiple design iterations using a co-design approach were beneficial to incrementally improve the course and consider multiple perspectives within the design process.

This paper develops a set of design principles to provide guidance to other practitioners who seek to improve their own courses.

The use of design-based research and mixed-method approaches that consider both student and teacher perspectives to examine the design of very large, foundational finance courses is novel.

This study aims to explore and classify the fragmentary findings of previous studies and improve understanding of the overall roles of supervisors in newcomer organizational socialization (NOS) and their relationships to NOS outcomes.

The study chiefly involves undertaking a literature review, with an emphasis on the perspective of human resource development (HRD). A structured literature review was conducted to identify and select articles through the Web of Science database.

Five important roles of supervisors during NOS – supporting training transfer, providing information, clarifying newcomers’ roles, facilitating sensemaking and providing feedback – were revealed from an examination of extant work. These roles markedly influence five different components of newcomers’ adjustment: task mastery, role clarification, organizational knowledge, social identification and social integration.

Although the concept of NOS used in this paper did not include all meanings of organizational socialization, the findings proposed key areas that require further study to enhance the understanding of supervisors’ roles for NOS.

The literature review suggests key efforts that supervisors should pursue to enhance the efficacy of newcomers’ adjustment. HRD professionals can use this information to design supervisor training programs aimed at enhancing supervisors’ knowledge and skills for successful NOS.

Studies have reported that supervisors markedly impact NOS and ultimately a newcomer’s success or failure. Relatively little work, however, has investigated how supervisors’ roles in the NOS process can enhance newcomers’ successful NOS outcomes.

Across the USA, local municipalities and providers struggle to reliably supply water and electricity when faced with severe weather events induced by climate change. Previous research suggests those at higher risk for experiencing the detrimental effects of climate change have higher climate-related concerns. Additionally, research demonstrates variation in trust in institutions and perceptions of environmental justice along racial lines, which can influence concern for access to resources. Informed by this research, the authors ask two questions: how do Oklahomans’ trust in institutions, environmental justice perceptions and global climate change risk perceptions differ based on race, and how do these factors influence concern for water and electrical infrastructure? The purpose of this study is to better understand Oklahomans’ trust in information from institutions, environmental justice perceptions, global climate change risk perceptions and concern for water and electrical infrastructure.

This study uses a series of nested regression models to analyze the survey responses of 2,687 Oklahoman adults. The data were pulled from Wave 3 of the Oklahoma Meso-scale Integrated Socio-geographic Network survey, which is part of the National Science Foundation EPSCoR S3OK project.

The findings demonstrate the complex interplay of riskscapes – or risk landscapes – that encompass institutional trust, perceptions of environmental justice, climate change and infrastructure in Oklahoma. The authors find evidence that education and income are better predictors of institutional trust and environmental justice than race among our respondents. Political ideology emerges as a significant predictor across all hypotheses.

This study contributes to the understanding of complex dynamics involving race, perceptions of environmental justice, trust in information from institutions, risk perceptions of climate change and concerns for water and electrical infrastructure in Oklahoma.

This paper aims to explore the past and future impacts of automation on family businesses, with a focus on the opportunities for human capital empowerment.

This paper draws upon a contemporary literature search to examine a range of scholarly and practitioner perspectives of the challenges and benefits of automation, exploring the evolvement towards hyperautomation and the empowerment of human capital in family businesses.

Automation, transforming to hyperautomation, general purpose artificial intelligence (AI) and beyond has the possibility of radically improving productivity. Fear of job obsolescence has been present since the birth of modern automation, and whilst some jobs are at risk of redundancy, a net gain towards higher-skilled labour is already evident. Family business leaders must be prepared to react appropriately to the accelerating war for talent by implementing a strategy for human capital empowerment.

This unique paper synthesises developments in automation and proposes a future perspective centred upon the empowerment of human capital in family businesses.

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.

The purpose of this case study was to complement existing weeding and retention criteria beyond the most used methods in academic libraries and to consider citation counts in the identification of important scholarly works.

Using a small sample of items chosen for withdrawal from a small liberal arts college library, this case study looks at the use of Google Scholar citation counts as a metric for identification of notable monographs in the social sciences and mathematics.

Google Scholar citation counts are a quick indicator of classic, foundational or discursive monographs in a particular field and should be given more consideration in weeding and retention analysis decisions that impact scholarly collections. Higher citation counts can be an indicator of higher circulation counts.

The authors found little indication in the literature that Google Scholar citation counts are being used as a metric for identification of notable works or for retention of monographs in academic libraries.

This study aims to empirically examine the influence of Islamic corporate social responsibility (ICSR) on social welfare moderated by financial fraud.

The method used was the mix method. The number of respondents was 410. They combined the moderate regression analysis with PROCESS Andrew F Hayes to test the research hypothesis. After conducting the survey, it was continued by conducting interviews with the village community and the head of the village.

The first finding of this study is that ICSR has a significant positive effect on social welfare. The second finding is that financial fraud weakens the influence of ICSR on social welfare. The results of the interviews also confirmed the two findings of this study.

The high level of bias in answering the questions is due to the low public knowledge of ICSR. In addition, the interviews still needed to involve the oil and gas companies and government.

The main implication is improving social welfare, especially for those affected by offshore oil drilling. Furthermore, stakeholders are more sensitive to the adverse effects of financial fraud. Finally, to make drilling companies more transparent and on target in implementing ICSR.

The main novelty in this research is using of the mixed method. In addition, applying financial fraud as a moderating variable is rarely studied empirically.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.