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Recent research and policy reports indicate public sector organizations struggle to leverage information technology-based performance measurement systems and fail to effectively evaluate performance beyond financial metrics. This study aims to focus on organizational factors that influence the assimilation of business intelligence (BI) systems into integrated management control systems and the corollary impact on improving business process performance within public sector organizations.

The complete Australian client list was acquired from a leading BI vendor; and the authors surveyed all public sector organizations, receiving 226 individual responses representing 160 public sector organizations in Australia. Using latent construct measurement, structural equation modeling (SEM)-partial least squares is used to test the theoretical model.

When top management promotes knowledge creation among the organization’s operational level employees and support their activities with strong BI infrastructure, the same knowledge and infrastructure capabilities that are critical to assimilation in private sector hold in the public sector. However, public sector organizations generally have difficulty retaining staff with expertise in new technologies and attracting new innovative staff that can leverage smart systems to effect major change in performance measurement. When top management effectively manages knowledge importation from external entities to counteract deficiencies, public sector organizations effectively assimilate BI knowledge into performance measurement yielding strong process performance.

When top management promotes knowledge creation among the organization’s operational level employees and support their activities with strong BI infrastructure, the same knowledge and infrastructure capabilities critical to assimilation in the private sector hold in the public sector. However, public sector organizations generally have difficulty retaining staff with expertise in new technologies and attracting new innovative staff that can leverage smart systems to effect major change in performance measurement. The research extends the theory behind organizational absorptive capacity by highlighting how knowledge importation can be used as an external source facilitating internal knowledge creation. This collaborative knowledge creation leads to affective assimilation of BI technologies and associated performance gains.

The results provide guidance to public sector organizations that struggle to measure and validate service outcomes under New Public Management regulations and mandates.

The results reveal that consistent with the philosophies behind New Public Management strategies, private sector measures for increasing organizational absorptive capacity can be applied in the public sector. However, knowledge importation appears to be a major catalyst in the public sector where the resources to retain skilled professionals with an ability to leverage contemporary technologies into service performance are often very limited. Top management team knowledge and skills are critical to effectively leveraging these internal and external knowledge creation mechanisms.

Government reforms have seen shifts from rules-based to principles-based risk regulatory governance. This paper examines the effects of principles-based risk regulatory reforms on public sector risk management (RM) and management control practices in public sector organizations (PSOs).

The principles-based regulation focuses on providing autonomy to PSOs while maintaining control over their actions without direct intervention. This resonates with Foucault's notion of how modern forms of governments operate. The research is informed by Foucault's concept of governmentality. The authors conducted a qualitative field study of an Australian PSO, gathering and analysing data from interviews, focus groups, and archival documents.

The findings show the capillary modes by which principles-based risk regulatory regime penetrates and works with management control practices in pursuit of regulatory goals within the PSO the authors studied. In addition, the authors find that the principles-based approach (focusing on autonomy) and rules-based approach (focusing on control) are not opposites in kind and effect but rather, autonomy should be understood as a central pillar of control. Furthermore, the findings show how cultural controls and formal controls are not in conflict but are interconnected in RM practices, with cultural controls providing control architecture for RM and formal control translating the control architecture into routines. Finally, the study provides insights into how enterprise risk management (ERM) provides capabilities for and routinizes RM practices in a PSO and the management control systems (MCS) that enabled this to occur.

The paper provides novel insights into how MCS are infiltrated, mobilized and deployed to enact principles-based risk regulatory reforms. These insights are useful for regulators, practitioners and researchers.

Big data clearly represent an important advance in information systems theory, but to describe it as “revolutionary” is premature. Similar technological breakthroughs, from online databases to ERP, were clearly modulated by advances in the organizational domain, including matters of structure, strategy and culture and arguably big data will be similar. The purpose of this paper is to encourage discussion of the wider implications of big data for the theory and practice of knowledge management.

This is a conceptual study based on critical analysis of the relevant literatures including those of organizational studies and management, big data and knowledge management.

The literature of big data emphasizes the application of algorithms to pattern analysis and prediction, resulting in data-driven decision-making, with data being the creator of value in organizations and societies. This would appear to render obsolete previous depictions of the “data-information-knowledge” relationship and, in effect, spell the end of knowledge management. However, big data literature largely ignores the organizational dimension and, significantly, the importance of frameworks, strategies and cultures for big data. As all of these are present in the literature of knowledge management, it would seem that big data have a long way to go to catch up and qualify even as a sub-discipline. Indeed, on the evidence, big data may well have a future as a contributor to and/or an element of knowledge management. Even for this to happen, however, major advances are required across the spectrum of big data technologies.

This is a position paper written as the precursor for an empirical study.

The paper offers a critical literature-based and knowledge management perspective on big data while pointing out the common thread that runs through decades of advances in information systems technologies.

Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.