Data breaches have become a formidable challenge for business operations in the twenty-first century. The emergence of big data in the ever-growing digital economy has created the necessity to secure critical organizational information. The lack of cybersecurity awareness exposes organizations to potential cyber threats. Thus, this research aims to identify the various dimensions of cybersecurity awareness capabilities. Drawing on the dynamic capabilities framework, the findings of the study show personnel (knowledge, attitude and learning), management (training, culture and strategic orientation) and infrastructure capabilities (technology and data governance) as thematic dimensions to tackle cybersecurity awareness challenges.

Purpose: Grounded on the technology-organization-environment (TOE) framework, the purpose of this paper is to develop a two-stage model of radio frequency identification (RFID) adoption in livestock businesses. RFID adoption is divided into two stages, acceptance and extension. It is argued that RFID adoption in livestock businesses is influenced by technological (interoperability, technology readiness), organizational (readiness, market scope), and environmental (competitive market pressure, data inconsistency) factors. Design/methodology/approach: From a qualitative field study, along with the support of existing literature, the authors developed a research model, which was then validated with survey data of 318 livestock businesses in Australia. Data analysis used partial least squares structural equation modeling. Findings: Empirical results showed that interoperability, organizational readiness, and competitive market pressure, and data inconsistency significantly influence acceptance of RFID technology in livestock businesses. In addition, the extended use of RFID is determined mainly by interoperability, technology readiness, organizational market scope, and data inconsistency. The results suggested differential effect of data inconsistency– it had a negative influence on RFID acceptance but a positive impact on the extent of its use. Originality/value: This is one of the first studies to examine RFID adoption as a two-stage process. The theoretical basis was based on TOE framework and the factors were developed from a field study. The results of this study will provide insights for different livestock industry including technologists, farm managers, and market players.

This study aims to examine the critical factors that could influence citizens in their decisions to adopt e-Government services. Based on the review of relevant literature, an extension of the UTAUT research model is developed. Through semi-structured interviews conducted in Indonesia with citizens who have adopted e-Government services, the research model is examined using thematic analysis. Results indicate that performance expectancy, effort expectancy, system quality, and perceived transparency are factors that significantly influence the adoption of e-government in Indonesia, whereas social influence, facilitating conditions, perceived security, information quality, and government encouragement are moderately significant factors. Meanwhile, ICT literacy is the least significant factor in the adoption of e-Government in Indonesia. Such findings are presented in the action priority matrix to offer public organisations with relevant suggestions on how the adoption of e-Government can be improved.

Purpose: Society's concerns about environmental degradation have tightened competitive pressure and brought new challenges to small firms. Against this backdrop, this study develops a decision model to determine a suitable configuration for entrepreneurial orientation to help small firms manage circular economy challenges and improve their performance.Design/methodology/approach: This study used a multi-study and multi-method approach. Study 1, through qualitative in-depth interviews, identified a portfolio of circular economy challenges and entrepreneurial-orientation components. Study 2 applied the quality function deployment technique to determine the most important components of entrepreneurial orientation. Study 3 adopted a fuzzy set qualitative comparative analysis to determine the best configuration for challenges and components.Findings: The findings reveal a set of challenges and identify the salient need to combine the negation of these challenges with the components of entrepreneurial orientation; this combination will improve the performance of small firms. The research extends the current knowledge of managing circular economy challenges and offers decision-makers insights into improving their resilience.Originality/value: The use of the dynamic capability view, together with the multi-study and multi-method approach, may lead to an appropriate reconfiguration of entrepreneurial orientation, which, to date, has received limited empirical attention in the small-business-management discipline.

Data-driven innovation (DDI) is a primary source of competitive advantage for firms and is a contemporary research priority. However, what facilitates the development of DDI has largely been understudied in literature. Through a systematic literature review, this study finds technological, organizational, and environmental variables under the TOE framework, which would drive effective DDI development. We thus develop a research model, which is tested using survey data from 264 Australian firms engaged in DDI development. The data have been analysed using both symmetric (partial least squares based structural equation modelling (PLS-SEM)) and asymmetric (fuzzy-set qualitative comparative analysis (fsQCA)) methods. The mixed method enhances the confidence in our empirical analyses of the antecedent variables of DDI development. PLS-SEM has revealed that technological readiness (i.e., data quality and metadata quality), and organizational absorptive capacity and readiness (i.e., technology-oriented leadership and availability of IT skilled professionals) affect DDI development. Our fsQCA results complement and extend the findings of PSL-SEM analysis. It reveals that quality of data and metadata, technology-oriented leadership, and exploitation capacity individually are necessary—but are not sufficient—conditions for high DDI development. Further, it identifies three different solutions each for small, medium, and large firms by combining the TOE factors. Additionally, this study suggests that the TOE framework is more applicable to small firms, on DDI context. Findings of our study have been related with theoretical and practical implications.