Companies, public authorities, and private Internet users are increasingly confronted with cyber risks. However, research and practice have focused particularly on cyber security in an organizational context. This ignores the fact that private individuals face cyber risks that differ from those they encounter as part of their job profile in an organizational context. Moreover, it is evident that private individuals behave differently concerning cyber risks, which can be explained by different context-dependent threat awareness as part of multi-dimensional cyber security competencies. Therefore, we extend the Cyber Security Domain Model (CSDM), which was initially established as the prerequisite for building cyber security competencies related to threats within an organizational context, to individuals. We draw on practitioner as well as academic sources to adjust and refine the two dimensions of (1) threat area and (2) threat event in the context of individuals, using a structured literature review.
With the Internet’s expansion, various online platforms have arisen, allowing people to express their views and influence electronic word-of-mouth (eWOM) for various brands. Depending on their personalities, some Internet users may express dissatisfaction or exhibit anti-brand behaviors when they receive products or services that don’t meet their expectations. Not all users, however, come to the brand’s defense, even if they disagree with the critics or anti-brand behaviors. Through a case study using netnography, we explored the influence of personality on online brand defense. We found that individuals seeking social recognition and self-validation are more likely to engage in online brand defense. Recognizing the impact of personality on online behavior can assist businesses and marketers in formulating strategies for fostering positive interactions with consumers.
The 21st century has earned the tragic sobriquet “The Century of Disasters” due to the escalating frequency, complexity, and severity of both natural and human-made calamities. Climate change, marked by an increasing frequency and severity of natural disasters, necessitates a paradigm shift for businesses operations, urging a transition from reactive to proactive and resilient strategies. Research in this area has become crucial, offering organizations vital insights to better prepare for and mitigate the impacts of future disasters. This chapter delves into the multifaceted impact of natural disasters on businesses, exploring how different disciplines are rising to meet these unique challenges. Key findings emphasize the need for flexible supply chains, robust disaster preparedness, and innovative financing mechanisms to mitigate risks and ensure business continuity. As the business landscape becomes increasingly shaped by the realities of disaster risk, it is clear that an interdisciplinary approach is essential. This chapter offers insights from the convergence of literature from Operations Management, Finance, Marketing, and Information Systems. Together, these findings offer a comprehensive framework for understanding and mitigating the complex challenges that disasters present. Pertinently, this chapter explores the burgeoning field of IS in disaster management, highlighting its critical role in saving lives, protecting assets, and building more resilient communities. While this discourse demonstrates the growing importance of IS in disaster management, a number of critical questions remain unanswered. These pave the way for future research opportunities, which are presented at the conclusion of this chapter.
The past few years have witnessed a rapid evolution in artificial intelligence (AI), marking the advent of a new cognitive era. Concurrently, academic interest in the organizational adoption and impacts of AI has surged, reflected in a diverse array of research across management disciplines. This chapter presents the Cognition Cube, a theoretical framework designed to synthesize emerging thematic trends in literature concerning AI’s firm-level impacts. Organized into temporal evaluations, foundational definitions of intelligent, agentic, and cognitive systems, and exemplar studies within the cube’s dimensions of AI, Human, and Task, this framework categorizes existing research and guides future inquiries. Highlighting areas such as cognitive reapportionment, GREAT economies, and innovation, the chapter aims to stimulate further research, anticipating significant growth in the study of AI’s organizational implications as we advance into the cognitive age.
This research-in-progress paper investigates the impact of Large Language Models (LLMs) on Digital Transformation (DT) across various industries, highlighting a paradigm shift in software customization and integration. Utilizing a mixed-methods approach, the study combines qualitative case studies and Qualitative Comparative Analysis (QCA) to explore the transformative effects of LLMs in business environments. Key findings reveal that LLMs significantly enhance customization capabilities, streamline data integration, and promote agile decision-making processes. This transition marks a critical evolution in DT strategies, offering new opportunities for operational efficiency and competitive advantage. The paper contributes vital insights to both academic discourse in technology management and practical business strategy, emphasizing the increasingly central role of LLMs in the digital-first business landscape.
