In recent years, big data has emerged as one of the prominent buzzwords in business and management.In spite of the mounting body of research on big data across the social science disciplines, scholars have offered little synthesis on the current state of knowledge. In this paper, we developed an integrated framework to link the multiple streams of research in fields of organisation, operations, marketing, information management and other relevant areas. Our analysis demonstrates how both structured and unstructured big data has been harnessed to inform organisational decisions and improve firm competitiveness. The review also indicates that big data has also unleashed novel challenges in term of security and privacy of personal data. In light of these, the study identifies and outlines the implications and directions for future research.

Although scholars in management recognize the value of harnessing big data to understand, predict and respond to future events, there remains little or very limited overview of how various analytics techniques can be harnessed to provide the basis for guiding scholars in studying contemporary management topics and global grand challenges raised by the COVID-19 pandemic. In this Methodology Corner, we present a review of the methodological innovations in studying big data analytics and how they can be better utilized to examine contemporary organizational issues. We provide insights on methods in descriptive/diagnostic, predictive and prescriptive analytics, and how they can be leveraged to study 'black swan' events such as the COVID-19-related global crisis and its aftermath's implications for managers and policymakers.

This research investigates the behavioural effects of firms' online activeness in influencing customer engagement in word-of-mouth communications. Using a large-scale field dataset of hotel reviews and managerial responses, this study empirically examines firm responsiveness in relationship to community members' participation in the online review posting. Novel findings are reported that response volume and speed are important for effecting firmcustomer interactions. This highlights a firm-leading influence on customers' word-of-mouth behaviour by identifying firm engagement as a motivational driver of customer engagement. It offers implications for researchers and practitioners with regard to social media marketing, in particular firm engaging in the online communication network by acting in an active and prompt manner.

It is understood that the mass media are a pervasive force in shaping the public's perceptions. This paper incorporates agenda-setting theory to explore whether and to what extent that the mass media can signal business failure. In an analysis of news coverage relating to Chinese underperforming listed firms over the period 2006-2017, it is demonstrated that firms whose stocks are put under "special treatment" status due to consecutive annual losses experience (*ST) greater news volume and lower news sentiment relative to other firms in the quarter in which the "delisting risk warning" announcements are made. Furthermore, *ST firms which are eventually delisted have a greater volume of news than other *ST firms, but we find no evidence that the sentiment of news relates to termination of listing. Our findings offer insights into the informativeness of the mass media and their agenda-setting effects in the business failure context.

Although big data, big data analytics (BDA) and business intelligence have attracted growing attention of both academics and practitioners, a lack of clarity persists about how BDA has been applied in business and management domains. In reflecting on Professor Ayre's contributions, we want to extend his ideas on technological change by incorporating the discourses around big data, BDA and business intelligence. With this in mind, we integrate the burgeoning but disjointed streams of research on big data, BDA and business intelligence to develop unified frameworks. Our review takes on both technical and managerial perspectives to explore the complex nature of big data, techniques in big data analytics and utilisation of big data in business and management community. The advanced analytics techniques appear pivotal in bridging big data and business intelligence. The study of advanced analytics techniques and their applications in big data analytics led to identification of promising avenues for future research.