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Decision making is inherently stressful since the decision maker must choose between potentially conflicting alternatives with unique hazards and uncertain outcomes. Whereas decision aids such as decision support systems (DSS) can be beneficial in stressful scenarios, decision makers sometimes misuse them during decision making, leading to suboptimal outcomes. The purpose of this paper is to investigate the relationship between stress, decision making and decision aid use.

The authors conduct an extensive multi-disciplinary review of decision making and DSS use through the lens of stress and examine how stress, as perceived by decision makers, impacts their use or misuse of DSS even when such aids can improve decision quality. Research questions examine underlying sources of stress in managerial decision making that influence decision quality, relationships between a decision maker’s perception of stress, DSS use/misuse, and decision quality, and implications for research and practice on DSS design and capabilities.

The study presents a conceptual model that provides an integrative behavioral view of the impact of a decision maker’s perceived stress on their use of a DSS and the quality of their decisions. The authors identify critical knowledge gaps and propose a research agenda to improve decision quality and use of DSS by considering a decision maker’s perceived stress.

This study provides a previously unexplored view of DSS use and misuse as shaped by the decision and job stress experienced by decision makers. Through the application of four theories, the review and its findings highlight key design principles that can mitigate the negative effects of stressors on DSS use.

The purpose of this paper is to emphasize the need to engender a positive attitude toward business analytics in order for firms to more effectively transform into data-driven businesses, and for business schools to better prepare future managers.

This paper develops and validates a measurement instrument that captures the attitude toward business statistics, the foundation of business analytics. A multi-stage approach is implemented and the validation is conducted with a sample of 311 students from a business school.

The instrument has strong psychometric properties. It is designed so that it can be easily extrapolated to professional contexts and extended to the entire domain of business analytics.

As the advent of a data-driven business world will impact the way organizations function and the way individuals think, work, communicate and interact, it is crucial to engage a transdisciplinary dialogue among domains that have the expertise to help train and transform current and future professionals.

The contribution provides educators and organizations with a means to measure and monitor attitudes toward statistics, the most anxiogenic component of business analytics. This is a first step in monitoring and developing an analytics mindset in both managers and students.

By demonstrating how the advent of the data-driven business era is transforming the DNA and functioning of organizations, this paper highlights the key importance of changing managers’ and all employees’ (to a lesser extent) mindset and way of thinking.

This paper aims to advance the international marketing debate by presenting the results of a structured literature review (SLR) focusing on Big Data implementation in customer relationship management (CRM) strategizing. It outlines past and present literature and frames a future research agenda.

The research analyzes papers published in journals from 2013 to 2020, deriving significant insights about Big Data applications in CRM. A sample of 48 articles indexed at Scopus was preliminarily submitted for bibliometric analysis. Finally, 46 papers were analyzed with content and a bibliometric analysis to identify areas of thematic specializations.

The paper presents a conceptual multilevel framework demonstrating areas of specialization emerging from the literature. The framework is built around four coordinated sequences of actions relevant to “why,” “what,” “who” and “how” Big Data is implemented in CRM strategies, thus supporting the conception and implementation of an internationalization marketing strategy.

Implications for the development of the future research agenda on international marketing arise from the comprehension of Big Data in CRM strategy.

The paper provides a comprehensive SLR of the articles dealing with models and processes of Big Data for CRM from an international marketing perspective. Despite these issues' relevance and the increasing literature focused on them, research in this area is still fragmented and underexplored, requiring more systematic and holistic studies.