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Alternative data is a term describing the data exhaust that organizations, especially asset managers, are using to develop insights about companies to give them a trading edge. As the use of this data becomes more prevalent, it is critical that business leaders understand how this kind of data can be used against their organizations. This viewpoint articulates some of the steps they will need to take to do this.

The methodology used in this viewpoint is a review of recent literature covering alternative data and its uses.

This paper describes the different ways in which alternative data is being used and cites surprising examples of how this can make companies vulnerable or threaten their reputation.

As an overview of selected examples from secondary sources, this paper is not a comprehensive treatment of the subject.

By studying the issues raised in the paper, business leaders can arm themselves with insights into the use of alternative data and mitigate reputational fallout from its use against their companies.

A better understanding of how alternative data is being used can help protect both individuals and social organizations from being treated inequitably and increase transparency in the use of large and hidden data sets.

To the best of the author’s knowledge, this is the first treatment of the use of alternative data from the perspective of corporate reputation.

The purpose of this paper is to examine the increasing use of data monitoring of employees by companies. As companies gather data on employees’ keystrokes and mouse clicks, as well as data on employees’ movements and interactions during the work day, they have an opportunity to strengthen the relationship of trust between employer and employee or weaken it. This viewpoint attempts to lay out some opportunities to have a positive outcome in this changing relationship.

The viewpoint looks at current practices in the monitoring of employees through secondary research into published sources to arrive at some hypotheses about how companies could create value for employees with the data they are gathering.

The viewpoint concludes that the dangers of poisoning the employer/employee relationship through intrusive monitoring and abuse of the data collected are very real. However, there is also an opportunity to empower employees with the very data being gathered on their behaviors and activities.

The findings are based largely on anecdotal insights and the views of individual corporate leaders and proponents of monitoring software. Primary research will be required to assess the actual opinions of employees about the monitoring software being used by their employers.

Those companies that embrace the empowerment of employees through the sharing of data being gathered and practice transparency about its gathering will gain competitive advantage as a favored employer.

Although there have been a significant number of articles describing the expansion in the digital monitoring of employees, the author is not aware of any discussion of the potential of this data gathering to produce positive results for employees.

Big data analytics has emerged as one of the most used keywords in the digital world. The hype surrounding the buzz has led everyone to believe that big data analytics is the panacea for all evils. As the insights into this new field are growing and the world is discovering novel ways to apply big data, the need for caution has become increasingly important. The purpose of this paper is to conduct a literature review in the field of big data application for humanitarian relief and highlight the challenges of using big data for humanitarian relief missions.

This paper conducts a review of the literature of the application of big data in disaster relief operations. The methodology of literature review adopted in the paper was proposed by Mayring (2004) and is conducted in four steps, namely, material collection, descriptive analysis, category selection and material evaluation.

This paper summarizes the challenges that can affect the humanitarian logistical missions in case of over dependence on the big data tools. The paper emphasizes the need to exercise caution in applying digital humanitarianism for relief operations.

Most published research is focused on the benefits of big data describing the ways it will change the humanitarian relief horizon. This is an original paper that puts together the wisdom of the numerous published works about the negative effects of big data in humanitarian missions.

This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.

The author adopts a grounded theory and conceptual approach to endeavour in this exploratory research.

The outcome shows a significant rise of big data in the tourism sector under three major dimensions, i.e. business, governance and research. And, some exemplary evidence of institutions promoting the use of big data and data science for sustainable tourism has been discussed.

The conceptualised interlinkage of concepts like IR 4.0, big data, data science and sustainable development provides a valuable knowledge resource to policy-makers, researchers, businesses and students.

The purpose of this paper is to offer the author's view about some of the challenges young Iberoamerican scholars face in order to build a successful research record.

This is an individual account of some of the most common barriers Iberoamerican scholars face when starting their academic career.

The paper presents some of the difficulties encountered by young scholars, such as motivation, lack of feedback, teaching load, and lack of resources and addresses these challenges in an almost intimate fashion.

The paper uses an idiosyncratic approach to the practical career obstacles faced by a young scholar outside the mainstream academic environment.

As big data (BD) has increasingly become an important tool for managers and researchers to transform sport management practices, the purpose of this research is to highlight diverse data sources and modern analytical techniques that will leverage BD as a means to advance scholarship in sport management.

A comprehensive review of existing BD literature in sport management outlines new perspectives on BD research method and the application of BD in sport management.

First, through a thorough review of the literature, a domain-specific conceptualization that incorporates the field's mission and priorities was developed. Second, potential data sources and different types of analytical opportunities was identified, highlighting strategies for developing methodological approaches that leads to novel research questions. BD analytics can allow for more flexibility in improving methodological capability to analyze data and, thus, provide more granular and predictive insights. Finally, this paper concludes with a discussion of BD's impact on three domains of sport management, whereby the organizations yield data-driven decisions.

BD has the potential to transform the sport management operations and bridges the research-practice gap. BD research in sport management is instrumental for accumulating new knowledge and/or testing existing theories, either in a deductive fashion or by taking an inductive approach, as the field embarks to advance scholarship.

The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.

The authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.

The results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.

The major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.

Managers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.

This is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.