Search results

This article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.

The author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.

After presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

As a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.

The paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

The paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.

This research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.

This paper aims to examine the dynamic impacts of the COVID-19 pandemic and government policy on real house price indices in five emerging economies, namely, Brazil, China, Thailand, Turkey and South Africa.

The authors use the local projection method with a panel data set of these countries spanning from January 2020 to July 2021.

The number of COVID-19 confirmed positive cases raised housing prices, whereas government containment measures reduced them. Both conventional and unconventional monetary policy implemented by central banks to cope with the COVID-19 helped increase housing prices. These effects were strengthened by the US monetary policy via globalized financial markets.

First, while previous researches typically concentrated on developed countries, the authors investigate emerging economies where proportionally more people were badly affected by the pandemic. Second, a panel data set of five emerging economies enabled the authors to examine the dynamic effects of the COVID-19 crisis on housing prices. Third, to the best of the authors’ knowledge, this is the first study evaluating the influences of easing monetary policy on housing prices in emerging economies during the pandemic.

In this study, the authors use the actor-network theory (ANT) as a theoretical framework to better understand constructing learning as part of the networking process to produce innovations. Focussing on the antecedents of innovation within three teams in an engineering company, the authors propose a framework to enhance understanding of the innovative processes. The authors apply ANT to examine how informal learning is distributed amongst human and non-human actors.

Based on 27 interviews in a large Australian engineering company, the authors' qualitative investigation shows that innovation can have very different antecedents. The authors mobilised ANT as the authors' vantage point to explore inanimate actors and their effect on social processes or, more specifically, networks and informal learning.

The authors propose a framework to better understand innovative processes by exploring the network aspects of non-human actors and their connection to learning. More specifically, findings contribute towards a more granulated understanding of how networks, learning and non-human actors contribute towards innovations in organisations.

This study has three significant implications for managers and organisations looking to improve their innovation processes. Firstly, fostering open communication is essential for developing successful innovation processes. Secondly, a close relationship with the customer and/or the final users has often been found to positively contribute to innovation processes. Finally, intrateam motivation is also critical when it comes to creating an environment that supports innovation processes.

Surprisingly, leadership, communication and motivation did not give the best innovative outcome as the authors expected. Challenging traditional theorisations, low teamwork spirit and high individual performance orientation were some of the powerful drivers of highly innovative teams.

The purpose of this paper is to investigate whether air pollution has significant impact on corporate cash holdings and financial leverage.

The data of 199 firms listed on Istanbul Stock Exchange during the period 2009–2020 is analyzed by using pooled ordinary least squares and two-step system generalized method of moments models.

The results indicate that firms in regions with high air pollution tend to increase cash level. In addition, the positive effect of air pollution on cash level is stronger and more significant for environmentally sensitive firms and firms with low operational and distress risk. The results also show insignificant effect of air pollution on financial leverage.

Firms in regions with high air pollution should conduct proactive environmental protection procedures and enhance their eco-efficiency instead of holding excess cash that could negatively affect financial performance. In this context, policymakers should provide financial facilities to firms located in regions with high air pollution and that have low ability to finance environmental investments. On the other hand, the environmental laws and regulations introduced by regulatory authorities can enhance the economic development and firm performance by decreasing the adverse influences of air pollution on corporate financial policies.

To the best of the author’s knowledge, this research is one of few that examines the impact of air pollution on corporate cash holdings and financial leverage in emerging markets.

This study aims to use the dual-continuum model of mental health to explore mental health in Australian construction apprentices from the perspective of key stakeholders in the apprenticeship model. In particular, this study explored how construction apprentices, Vocational Education and Training (VET) teachers, industry employers and mental health workers understood the construct of mental health, factors associated with the dimension of psychological distress/symptoms of mental illness, and factors associated with the dimension of mental wellbeing.

This study used an exploratory qualitative research design. Data from 36 semi-structured interviews were analysed using thematic analysis. Participants comprised 19 Australian construction apprentices, 5 VET teachers, 7 industry employers and 5 mental health workers.

In total, 14 themes were generated from the data set. Participants across stakeholder groups reported a limited understanding about mental health. Participants cited a range of negative personal, workplace and industry factors associated with psychological distress/symptoms of mental illness, but only reported a few factors associated with mental wellbeing.

To the best of the authors’ knowledge, this study is one of the first to use the dual-continuum model of mental health to explore the mental health of Australian construction apprentices, and to explore the factors associated with both dimensions of this model from the perspective of key stakeholders in the Australian construction apprenticeship model.