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The purpose of this study is to investigate how digital technologies are used for facilitating knowledge sharing and decision-making through enhanced coordination and communication and their impact on job performance in organizations.

A conceptual model is developed within the background of the social capital theory through a comprehensive review of the related literature for exploring how digital technologies can improve knowledge sharing and decision-making via enhanced communication and coordination between individuals in organizations for better job performance. This model is then tested and validated based on structural equation modeling of the collected survey data in Australia.

This study shows that digital technology enhanced coordination and communication have significant impact on knowledge sharing. It finds out that digital technology driven coordination significantly influences decision-making and digital technology driven knowledge sharing significantly influences decision-making. Furthermore, this study reveals that enhanced decision-making and knowledge sharing can lead to better job performance in organizations.

To the best of the authors’ knowledge, this study is the first attempt to explore the role of digital technologies in enhancing knowledge sharing and decision-making for better job performance in a digitalized working environment in organizations. The validated model can be used as the foundation to further investigate the changing role of digital technologies in driving knowledge sharing for better performance of individuals and competitive advantages of organizations.

Public universities worldwide are under growing pressure to increase efficiency. Understanding how teaching and research contribute to the overall efficiency of university operations is of great importance for universities to improve their performance. This paper aims to discuss this issue.

This paper adopts a holistic approach to evaluate university efficiency from three perspectives including overall university operations efficiency, university teaching efficiency and university research efficiency. It applies the technique of data envelopment analysis to 36 Australian universities during the period 2011–2015 to evaluate their relative efficiency from these three perspectives. A strategic group analysis is further conducted for exploring the source of inefficiency of an individual university in its respective strategic group.

This study reveals that Australian universities maintain a comparatively high level of efficiency in terms of overall operations and research during the period 2011–2015. Teaching efficiency, however, is underwhelming during this period. It further shows that universities with low efficiency seeking to improve their overall operations efficiency can allocate the limited resource to teaching instead of research.

This study is crucial to both Australian government and Australian universities. The government is provided with the information about the optimum performance levels for universities under certain fixed resource. As a result, resources or funding can be allocated based on the performance ranking. The efficiency information is also in demand among Australian universities. In order to successfully strive for more funding from the federal government in an environment of increased competition, universities need to not only know their relative position among their peers, but also get guidelines on how to improve their performance.

The novelty of this study lies in the decomposing of efficiency models to identify inefficiencies in university operations. Such a study provides individual universities with valuable information on how they can make full use of their resources to improve their efficiency in an increasingly competitive environment.

Understanding the critical determinants for the adoption of electronic markets (e-markets) is significant for the development of sustainable electronic business. The purpose of this paper is to investigate the critical determinants for the adoption of e-markets in Australian small- and medium-sized enterprises (SMEs) for electronic business.

A comprehensive review of the related studies is conducted. That leads to the development of a conceptual model for exploring the critical determinants for the adoption of e-markets in Australian SMEs. Such a model is then tested and validated using structural equation modelling on the survey data collected, leading to the identification of the critical determinants for e-market adoption in Australian SMEs.

The study reveals that perceived direct benefit, perceived trust, top management support and external pressures are critical for the adoption of e-markets in Australian SMEs. Perceived indirect benefit and organization readiness are insignificant for the adoption of e-markets.

This paper contributes to existing electronic business research by enriching the understanding of the critical determinants for the adoption of e-markets in Australian SMEs. Such a study provides government departments, e-market operators and SMEs with practical guidelines for the better use of e-markets in electronic business.

Digital technologies have been transforming the traditional workplace and reshaping how work is designed, performed and managed in organizations. This makes understanding digital work and its impact on job performance critically important. This study investigates the impact of digital work on job performance in organizations from the perspective of technology affordance.

A comprehensive review of the related literature has been conducted, leading to the development of a conceptual model for exploring the impact of digital work on job performance from the perspective of technology affordance. Such a model is then tested and validated using structural equation modelling on the survey data collected in Australia.

The study shows that the use of digital technologies significantly improves coordination and knowledge sharing between individuals, leading to better work–life balance and improved job performance. Furthermore, the study reveals that the use of digital technologies that can enhance communication and decision-making does not significantly influence work–life balance and job performance in digital work.

This study presents a comprehensive investigation of the impact of digital work on job performance in organizations from the perspective of technology affordance. It explores the changing role of digital work in transforming existing working practices in organizations, and how different technology affordances in digital work can be actualized for improving work–life balance and job performance in a digitalized working environment.

Understanding the privacy concerns of individuals in the adoption of contact tracing apps is critical for the successful control of pandemics like COVID-19. This paper explores the privacy paradox in the adoption of contact tracing apps in Australia.

A comprehensive review of the related literature has been conducted, leading to the development of a conceptual model based on the privacy calculus theory and the antecedent-privacy concern-outcome framework. Such a model is then tested and validated using structural equation modelling on the survey data collected in Australia.

The study shows that perceived benefit, perceived privacy risk and trust have significant influences on the adoption of contact tracing apps. It reveals that personal innovativeness and trust have significant and negative influences on perceived privacy risk. The study further finds out that personal innovativeness is insignificant to perceived benefit. It states that perceived ease of use has an insignificant influence on perceived privacy risk in the adoption of contact tracing apps.

This study is the first attempt to use the privacy calculus theory and the antecedent–privacy concern–outcome framework for exploring the privacy paradox in adopting contact tracing apps. This leads to a better understanding of the privacy concerns of individuals in the adoption of contact tracing apps. Such an understanding can help formulate targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control through effective contact tracing for better emergency management.

This study aims to explore the adoption of contact tracing apps through a hybrid analysis of the collected data using structural equation modelling (SEM) and artificial neural networks (ANN), leading to the identification of the critical determinants for the adoption of contact tracing apps in Australia.

A research model is developed within the background of the unified theory of acceptance and use of technology (UTAUT) and the privacy calculus theory (PCT) for investigating the adoption of contact tracing apps. This model is then tested and validated using a hybrid SEM-ANN analysis of the survey data.

The study shows that effort expectancy, perceived value of information disclosure and social influence are critical for adopting contact tracing apps. It reveals that performance expectancy and perceived privacy risks are indirectly significant on the adoption through the influence of perceived value of information disclosure. Furthermore, the study finds out that facilitating condition is insignificant to the adoption of contact tracing apps.

The findings of the study can lead to the formulation of targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control for better emergency management.

This study is the first attempt in integrating UTAUT and PCT for exploring the adoption of contact tracing apps in Australia. It combines SEM and ANN for analysing the survey data, leading to better understanding of the critical determinants for the adoption of contact tracing apps.

Improving digital work experience is critical for the job performance of individuals and the competitiveness of organizations due to their increasing use. This paper investigates how organization support affects the digital work experience of individuals differently depending on their levels of information technology (IT) identity.

Drawing upon the IT identity literature and the conservation of resources (COR) theory, a conceptual model is developed, tested and validated using the data collected in Australia through an experimental design in which IT identity is manipulated.

This study reveals a nuanced impact of organization support on shaping digital work experience. Specifically, it finds that technical support is more effective in improving the digital work experience of individuals with a high level of IT identity, whereas well-being support is more effective in enhancing the digital work experience of individuals with a low level of IT identity.

This research contributes to the IT identity literature by introducing a novel experimental design to manipulate IT identity in the digital work context. It also contributes to the digital work literature by introducing a resource perspective for identifying well-being support, technical support and IT identity as the key resources in shaping digital work experience and calling for attention to IT identity as a boundary condition on the effectiveness of organization support. The findings can help organizations formulate better strategies and policies to improve digital work experience by providing tailored support to individuals with different levels of IT identity.

Effectively evaluating the efficiency of individual e-markets for better understanding the efficiency-oriented critical drivers for individual e-markets is of great significance to the development of electronic business. The purpose of this paper is to develop an approach through adequately integrating data envelopment analysis (DEA) and bootstrapped Tobit regression analysis for identifying the efficiency-oriented critical drivers on the development of e-market in electronic business.

A review of the related literature is conducted for adequately formulating the e-market evaluation problem. DEA is appropriately used for assessing the efficiency of available e-markets, leading to the identification of the efficient e-market. Tobit regression analysis is then employed to examine the outcome of the DEA analysis for identifying the efficiency-oriented critical drivers in the development of e-markets in electronic business.

A better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business can be achieved with the use of the developed approach. Such understanding is built on the identification of the efficiency-oriented critical drivers on the development of e-market in electronic business.

This paper develops a novel approach for better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business. The adoption of this approach helps existing e-markets improve their efficiency by focussing on the efficiency-oriented critical drivers and provide new players in e-markets with guidelines for developing their efficient e-markets.

Artificial intelligence (AI) has been touted as one of the viable solutions to address urban mobility issues. Despite a growing body of research on AI across various sectors, its use in the mobility sector remains underexplored. This study addresses this limitation by investigating AI applications and identifying the AI material properties and use cases that offer mobility-specific affordances.

Although AI applications in mobility are growing, academic research on the subject has yet to catch up. Therefore, we follow a systematic review and analysis of practitioner literature. We conducted a comprehensive search for relevant documents through Advanced Google and OECD databases and identified 173 sources. We selected 40 sources published between 2015 and 2022 and analysed the corpus of evidence through abductive qualitative analysis technique.

The analysis reveals that mobility organisations are implementing various AI technologies and systems such as cameras, sensors, IoT, computer vision, natural language processing, robotic process automation, machine learning, deep learning and neural networks. These technologies offer material properties for sensing mobility objects and events, comprehending mobility data, automating mobility activities and learning from mobility data. By exploiting these material properties, mobility organisations are integrating urban mobility management, personalising and automating urban mobility, enabling the smartification of infrastructure and asset management, developing better urban transport planning and management, and enabling automatic driving.

The study contributes a mid-range theory of the affordances of AI for mobility (AI4M) at the infrastructure, operation and service levels. This contribution extends the existing understanding of AI and offers an interconnected perspective of AI affordances for further research. For practitioners, the study provides insights on how to explore AI in alignment with organisational goals to collectively transform urban mobility to be affordable, efficient and sustainable.

Mobility as a service (MaaS) is a new model of bundling personal transport options from multiple providers to provide frictionless service. The model integrates information and service to enable users to search, book and pay through a single digital platform. The aim of MaaS is to minimize individual car ownership and revolutionize personal mobility habits in favour of sustainable modes. Thus, it is important to understand consumers' readiness for MaaS. This study explains the factors that influence MaaS adoption.

A comprehensive review of the related literature has been conducted, leading to the development of a conceptual model for investigating the key factors that influence MaaS adoption. The model draws upon the digital platform, schema congruity and planned behaviour theories. The model is then tested using structural equation modelling and survey data collected from 331 respondents.

The findings indicate that MaaS information schema congruity, the digital platform's personalizability, customizability, functional integration, network integration and governance of data together with attitude towards MaaS and subjective norm concerning MaaS influence MaaS adoption. Furthermore, MaaS digital platform expectation and MaaS information schema congruity contribute to users' attitude towards MaaS use.

The paper highlights the design and informational attributes of MaaS platforms that influence their adoption and contributes an integrated research model that links digital platform characteristics, behavioural factors and information schema congruity. Future research can use the constructs and measures we developed in this study to build deeper understanding of what contributes to the success of digital platforms.