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This paper aims to communicate the relevant management model with optimal performance in the collection of construction resources (human, non-human), supervision of workers and activities in the development of adequate and quality school infrastructure facilities.

The study employed a mixed methods research approach in collecting and analysing research findings. Semi-structured face-to-face interviews and questionnaires which consisted of closed questions were the data collection tools. Numerical data collected were processed and analysed by using quantitative methods and techniques such as descriptive analysis, whereas text data were subjected to content analysis.

The findings revealed that the Post-New Public Management (PNPM) is relevant in the collection of construction resources and suitable for the supervision of workers and tasks towards the development of adequate and quality school infrastructure facilities. Based on the evidence generated, the PNPM model was recommended to be adapted to collection of construction resources and supervision of workers and activities.

This paper highlights the need for construction committees and other education policy implementers to adapt a relevant management model in realising optimal performance in the development of adequate and quality school infrastructure facilities.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

The 50th anniversary of Fox's Beyond Contract and Man Mismanagement coincides with another vital contribution to the sociology of work from 1974: Braverman's Labor and Monopoly Capital. This article analyses these two scholars' complementary approaches to job design and the extent to which Fox's ideas influenced subsequent labour process thought.

The article's methodological approach is a historiographical reading of Fox and Braverman's thought in the context of their times and later scholarship.

The article demonstrates that despite some noteworthy overlap with Braverman concerning scientific management, Fox's insights were marginal to later iterations of labour process analysis. It delves into the reasons for this relative neglect, providing an understanding of the dynamics at play.

This paper's value lies in its combined industrial relations and labour process historiography. It offers a fresh perspective on Alan Fox's relationship to the latter field of study.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

Over the last two decades, there has been a significant increase in incivility within the higher education sector, potentially due to mounting pressure and demands on academics, both collectively and individually. The effects on various aspects of academia, such as knowledge and learning, however, remain largely unexplored. The purpose of this research is to fill the gap by performing a theoretical trend analysis and subsequently empirically investigating the impact of workplace incivility on research scholars’ learning engagement and knowledge sharing intentions, including the mediating role of self-esteem.

This study uses a three-stage methodological process: first, a thorough theoretical (bibliographic) analysis of scientific publications, using Biblioshiny, to identify the trends of workplace incivility; second, an empirical, qualitative exploration of the emergent themes and subthemes based on 102 in-depth interviews with research scholars, using NVivo 12 Plus; and third, quantitative testing, using 154 responses and structural equation modeling.

The authors verify a visible negative association between incivility and learning engagement, incivility and knowledge sharing intentions as well as self-esteem’s mediating effect on this relationship. Also, the thematic analysis revealed three distinct themes: the type of incivility; reasons for such incidences; and the impact of such incidences on research scholars.

The research bears implications both to theory and practice. Regarding the former, the gravity and graveness of incivility versus knowledge and learning, within the academic workplace environment, are not simply highlighted, but analyzed and refined, with explicit findings of both scholarly and practicable worth; that also provide solid foundations and avenues for future research.

Further to its primary findings, the research contributes to extant knowledge by elucidating and explicating the topic, both theoretically and empirically, as well as by presenting implications for theory and practice. Regarding practical implications, this research sheds light on how to develop an appropriate organizational culture that facilitates learning engagement and increases knowledge sharing intentions, by nurturing the identified explicit and underlying motivators of civility.

Companies avoid taxes in a variety of ways and use different methods to do that, one of the most common being earnings management. The purpose of this paper is to investigate whether companies manipulate their financial data in order to reduce taxes paid.

We considered a sample of 63 listed Romanian companies for the period 2016–2021. The Beneish model was used for estimating earnings management, and the effective tax rate was used to measure tax avoidance. The analysis was carried out using regression analysis in Stata13 software.

The findings of the research indicate a negative and statistically significant association between effective tax rate and earnings management, implying that one of the main reasons why companies manipulate their earnings to reduce tax burden and avoid taxes. Moreover, our results show that return on assets (ROA) has a statistically significant negative influence on the effective tax rate. Furthermore, our analysis reveals that firm size, growth, and Big4 audit have no effect on effective tax rate.

Because it analyzes concrete cases using financial data and provides some recommendations for addressing the issue of tax avoidance, this work is useful in advancing both quantitative and qualitative research on this topic. This research is relevant for businesses, governments, regulators, audit professionals and investors.

The study, by analyzing concrete cases using reported financial data, contributes in filling the gap within the literature that results from a lack of scientific research on the relationship between tax avoidance and earnings management, and then it clarifies the nature of the causal connection between them. Moreover, it considers a combination of firm related variables including performance, size and also audit quality.

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.

The author employed a five-step approach: Data (e.g., qualitative primary and secondary data) collection (about a major project at the examined organisation), Critical thinking (in order to determine the dilemma), Setting learning objectives (e.g., with respect to the Bloom's taxonomy), Testing (in order to confirm the teaching plan) (e.g., with research assistants and doctoral candidates), and Ensuring clarity (e.g., especially for the case narrative).

The site manager at a UNESCO World Heritage Site by the name Ephesus in Türkiye (Turkey) was considering who would update the site management plan. UNESCO was regularly asking for updates. Would site management outsource the management plan from a firm? For example, the site management had had an outside firm develop the management plan and Ephesus had become a UNESCO World Heritage Site. Otherwise, would the site management rely on their own experience this time? Was there another way?

The educators could use the case study to introduce graduate students to “the value conception” in “marketing management” courses and to “the social exchange school of thought” in “marketing theory” courses. The learning objectives develop over the tension between owning and outsourcing main responsibilities of a scientific field as well as the tension between claims and objective evaluations. “The value conception” in “the social exchange school of thought” could improve planning in favour of humanity in a way that the United Nations could recognise (e.g., “value-based planning”). Corresponding discussions motivate a main question about the future: What is marketing for?

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.