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Open-access repositories (OARs) are essential for openly disseminating intellectual knowledge on the internet and providing free access to it. The current study aims to evaluate the growth and development of OARs in the field of technology by investigating several characteristics such as coverage, OA policies, software type, content type, yearly growth, repository type and geographic contribution.

The directory of OARs acts as the source for data harvesting, which provides a quality-assured list of OARs across the globe.

The study found that 125 nations contributed a total of 4,045 repositories in the field of research, with the USA leading the list with the most repositories. Maximum repositories were operated by institutions having multidisciplinary approaches. The DSpace and Eprints were the preferred software types for repositories. The preferred upload content by contributors was “research articles” and “electronic thesis and dissertations”.

The study is limited to the subject area technology as listed in OpenDOAR; therefore, the results may differ in other subject areas.

The work can benefit researchers across disciplines and, interested researchers can take this study as a base for evaluating online repositories. Moreover, policymakers and repository managers could also get benefitted from this study.

The study is the first of its kind, to the best of the authors’ knowledge, to investigate the repositories of subject technology in the open-access platform.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

This study aims to investigate the factors associated with the intention to use information technology in audit (ITIA) in Iraq.

The study uses a quantitative approach based on a questionnaire survey of 186 respondents. The study population includes respondents who are board members, senior executives, internal auditors and information technology (IT) assistants in various Iraqi organizations from different sectors. Structural equation modeling has been used to estimate the results.

The findings exhibit that most auditors in Iraq use basic IT software. However, among several specialized and advanced IT audit software packages, only generalized audit software is used by about 20%. The results also indicate that social factors significantly and positively impact auditors’ and practitioners’ perceptions of ITIA use. Moreover, the results reveal that companies and auditors who use or audit complex accounting systems perceive higher benefits and intent to adopt ITIA. However, the results report that organizational support, professional support, competency and IT education have an insignificant effect on ITIA adoption.

The originality of the present research lies in several aspects. First, the research study focuses specifically on Iraq, which is an emerging and less developed country influenced by social and economic. This research context provides a unique perspective and contributes to the understanding of ITIA adoption in less developed countries. The study investigates how external factors, including social and external pressure and the support of government professional bodies, affect the adoption of ITIA. Further, it assesses the influence of firms’ specific factors such as management support, level of competency and complexity of accounting information systems. Second, the study uses a quantitative approach with a questionnaire survey from various Iraqi organizations and sectors. The specific sample composition adds originality by capturing insights from different levels of organizational hierarchy and diverse professional backgrounds. Third, the findings shed light on the current IT usage in auditing practices in Iraq, highlighting that most auditors use basic IT software and the limited adoption of specialized IT audit software packages. Finally, the study’s originality is also reflected in its contribution to expanding knowledge on the perceived benefits and challenges associated with ITIA adoption in less developed countries. By emphasizing the need for broader awareness of emerging technology-enabled auditing software and considering the unique characteristics of less developed countries, the research provides valuable insights and implications for practitioners, policymakers and researchers.

This research delineates the interdependencies between e-service quality (e-SQ), product quality (PQ) and food biosafety measures (FBM) in shaping consumer satisfaction and loyalty within the online food delivery services (OFDS) landscape. Anchored by the technology acceptance model (TAM) and the theory of planned behavior (TPB), the study integrates these frameworks to examine how perceived service efficiency, reliability, product appeal and biosafety protocols contribute to overall consumer trust and repurchase intentions.

Surveys were conducted on several 100 online food delivery app users, ages 20 to 64, in major cities in Colombia, which provided data for structural equation modeling analysis.

The analysis revealed that reliable, responsive service and appealing food presentation significantly influence consumer perceptions of behind-the-scenes safety protocols during delivery. Strict standards around mitigating contamination risks and verifiable handling at each point further engender trust in the platform and intentions to repurchase among users. The data cement proper food security as pivotal for customer retention.

Quantitatively confirming biosafety’s rising centrality provides an impetus for platforms to integrate and promote integrity, safety and traceability protection as a competitive differentiator.

The study’s originality lies in its comprehensive exploration of the OFDS quality attributes and their direct impact on consumer loyalty. Besides, it offers valuable insights for both academic and practical implications in enhancing service delivery and marketing strategies.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

Different studies have been conducted on the relationship between technological capability and firm performance. These studies obtain different values for the relationship, known as heterogeneous results. The purpose of this paper is to analyze the relationship between technological capability and firm performance and its statistical between-study heterogeneity.

In order to analyze all the results from this relationship that were found in the literature, we adopted the literature review with a meta-analytic method. We consulted the Scopus and Web of Science databases, which returned, after the application of inclusion criteria, 23 primary studies with data from 5,882 manufacturing firms.

We observed that technological capability and performance are positively related; however, the results regarding this relationship are heterogeneous. We discovered four possible sources of statistical between-study heterogeneity: (i) the statistical between-study heterogeneity of the variables to measure technological capability and performance; (ii) orientation of the thematic approach – some illustrate the relationship between technological capability and performance using mathematical and theoretical models, while others examine the relationship between technological capability and performance and propose implications pertaining to that relationship; (iii) the source of data for primary studies and (iv) the context in which this relationship is observed.

It is necessary to standardize a set of variables through which technological capability and performance are evaluated so that results and implications can be usefully compared between countries and industrial sectors.

The contribution to knowledge is identifying the statistical between-study heterogeneity on the relationship between technological capabilities and firm performance, as well as its potential sources.

This study aims to understand workplace conflict outcomes (WCO) literature and identify the research gaps by mapping its knowledge base and theoretical evolution.

This study combines bibliometric and qualitative analysis and encompasses 1,043 Scopus-indexed documents published between 1972 and 2022. The bibliometric analysis used VOSviewer, Excel and Tableau software for descriptive statistics, citation and co-citation analyses of publication patterns, authors, documents and journals. The qualitative analysis critiqued main theoretical perspectives and topical interests.

This study revealed a significant increase in literature after 2000, with authors representing 70 societies, primarily the USA, China, Australia, Canada and the Netherlands. Influential authors and their canonical articles were identified, including Jehn, De Dreu, Spector, Amason and Pelled. Highly cited articles focused on task, relationship, role and process conflict. Four main theoretical schools were categorized: conflict type paradigm, individual differences, conflict cooccurrence and conflict dynamics. Influential journals spanned psychology, management, negotiation and decision-making and business and marketing fields, including JAP, AMJ, ASQ, JM, JOB, AMR, IJCMA and OS.

This study provides implications for future bibliometric analyses, theoretical and empirical studies, practitioners and society based on its quantitative and qualitative findings.

To the best of the authors’ knowledge, this study represents the first bibliometric review of WCO literature, serving as a baseline for tracking the field’s evolution and theoretical advancements.

This paper aims to design a hybrid model of knowledge-based performance management system (KBPMS) for facilitating Lean Six-Sigma (L6s) application to increase contractor productivity without compromising human safety in Indonesian upstream oil field operations that manage ageing and life extension (ALE) facilities.

The research design applies a pragmatic paradigm by employing action research strategy with qualitative-quantitative methodology involving 385 of 1,533 workers. The KBPMS-L6s conceptual framework is developed and enriched with the Analytical Hierarchy Process (AHP) to prioritize fit-for-purpose Key Performance Indicators. The application of L6s with Human Performance Modes analysis is used to provide a statistical baseline approach for pre-assessment of the contractor’s organizational capabilities. A comprehensive literature review is given for the main pillars of the contextual framework.

The KBPMS-L6s concept has given an improved hierarchy for strategic and operational levels to achieve a performance benchmark to manage ALE facilities in Indonesian upstream oil field operations. To increase quality management practices in managing ALE facilities, the L6s application requires an assessment of the organizational capability of contractors and an analysis of Human Performance Modes (HPM) to identify levels of construction workers’ productivity based on human competency and safety awareness that have never been done in this field.

The action research will only focus on the contractors’ productivity and safety performances that are managed by infrastructure maintenance programs for managing integrity of ALE facilities in Indonesian upstream of oil field operations. Future research could go toward validating this approach in other sectors.

This paper discusses the implications of developing the hybrid KBPMS- L6s enriched with AHP methodology and the application of HPM analysis to achieve a 14% reduction in inefficient working time, a 28% reduction in supervision costs, a 15% reduction in schedule completion delays, and a 78% reduction in safety incident rates of Total Recordable Incident Rate (TRIR), Days Away Restricted or Job Transfer (DART) and Motor Vehicle Crash (MVC), as evidence of achieving fit-for-purpose KPIs with safer, better, faster, and at lower costs.

This paper does not discuss social implications

This paper successfully demonstrates a novel use of Knowledge-Based system with the integration AHP and HPM analysis to develop a hybrid KBPMS-L6s concept that successfully increases contractor productivity without compromising human safety performance while implementing ALE facility infrastructure maintenance program in upstream oil field operations.