Business Horizons最新文献

Digital Transformation (DT) is more than simply integrating a new digital technology into the organization. Despite a growing volume of research, however, there is little coverage of the characteristics of DT leadership. Using a grounded approach, where 16 practitioner voices are central to the theorizing output, we present 10 DT leadership characteristics. Each characteristic links what action a DT leader needs to take and how a DT leader enables that action. We also asked 30 DT leaders to evaluate the importance of each of the 10 DT leadership characteristics. Our approach strengthens the relevance for practitioners striving for the best possible DT initiative outcome. For example, prefacing each DT leadership characteristic with “Are we…?” Encourages DT leaders to guide conversations with organizational stakeholders by reflecting on the realities of their DT initiative and highlighting potential gaps in their organizational thinking.

Digital leadership involves dealing with complex challenges and anticipating trends that arise from emerging technologies. Amid the accelerated pace of digital transformation, consequences such as technostress have become apparent to organizations and their leaders. Emotional intelligence (EI) is an essential characteristic for enabling digital leaders to hone the necessary skills to lessen employees’ technostress by developing higher levels of consciousness of emotions—both one’s own and those of others. By synthesizing research-based knowledge of EI and leadership, we contribute to a broader understanding of competency requirements for digital transformation by bringing employees and the role of digital leadership through EI into the picture. This article also presents new EI strategies for digital leaders to mitigate employee technostress in digital transformation via communication, transparency, and trust.

Digital transformation has garnered significant interest within the research and business communities, and has become an umbrella concept to address the multiple technological, strategic, operational, and leadership dimensions involved in digitally enabled organizational renewal. Such transformation spans beyond mere automation of existing practices to a radical change of business scope. Despite this increased attention, a shared understanding of exactly what digital transformation encompasses and how a digital transformation initiative can be defined and led is still underdeveloped. This article aims to contribute to this research gap by identifying the multifaceted conceptual and applied dimensions of digital transformation and integrating them into a single, unifying framework. Based on a synthesis of extensive yet fragmented literature and feedback from domain experts, we present a conceptual map (i.e., a canvas) for successful digital transformation initiatives. In addition, we identify the key elements through which one can lead implementation (i.e., roles, competencies, behaviors, and enablers). The article contributes both to academia—by advancing the meaning and constituent factors of digital transformation—and practitioners, with the formulation of a conceptual tool for managers engaged in a systemic design of digital transformation initiatives.

Financial institutions operate in a competitive, complex, and uncertain environment. A series of changes—many accelerated by the COVID-19 pandemic—demand innovative movements from the organizations that operate in the sector. The emergence of new business models (e.g., fintecs) requires a realignment of the capabilities of traditional organizations, such as banks. Indeed, internal adaptations and the formulation of market strategies focused on a digital user are part of the current narrative. But how can it be executed? This article explores the relationship between dynamic capabilities and digital transformation. In summary, we present insights about how dynamic capabilities can drive innovation in traditional financial institutions based on the challenges brought by digital transformation. Starting from a Brazilian case study, we identified that external and internal contextual factors—especially the political-legal environment and cultural and governance issues—are necessary for stimulating the dynamic capabilities that should be addressed for digital transformation. Finally, we propose a framework that summarizes how dynamic capabilities enable the guidance of traditional banks amid challenges caused by digital transformation.

Chatbots such as ChatGPT are conversational agents that play an important role in many sectors. They are highly sophisticated artificial intelligence (AI) agents increasingly integrated into organizational functions ranging from customer support to recruitment and professional development. Alongside the increasing adoption of chatbots is an increasing focus on diversity, equity, and inclusion (DEI). This article presents a series of chatbot examples and discusses their associated DEI implications, such as those related to AI bias. From the cases reviewed in this article, we extract a framework of DEI safeguards, which includes input safeguards, design safeguards, and functional safeguards. This framework can be used by those involved in developing AI based chatbots or managing their use to ensure that chatbots support, rather than weaken, organizational DEI initiatives and strategies.

Advances in large language model (LLM) technology enable chatbots to generate and analyze content for our work. Generative chatbots do this work by predicting responses rather than knowing the meaning of their responses. In other words, chatbots can produce coherent-sounding but inaccurate or fabricated content, referred to as hallucinations. When humans uncritically use this untruthful content, it becomes what we call botshit. This article focuses on how to use chatbots for content generation work while mitigating the epistemic (i.e., the process of producing knowledge) risks associated with botshit. Drawing on risk management research, we introduce a typology framework that orients how chatbots can be used based on two dimensions: response veracity verifiability and response veracity importance. The framework identifies four modes of chatbot work (authenticated, autonomous, automated, and augmented) with a botshit-related risk (ignorance, miscalibration, routinization, and black boxing). We describe and illustrate each mode and offer advice to help chatbot users guard against the botshit risks that come with each mode.

Generative artificial intelligence (GenAI) has long been considered a technology for the future. With the release of the chatbot ChatGPT 4, many now feel the future has arrived. Long in gestation, this new technology promises many benefits to humankind, but worries persist that as AI technology scales and comes to rival or exceed human intelligence, the servant may become the master. Amid such hyperbole, the more nuanced trajectories of this technology have been neglected. In this article, we use the Trajectories of Technology (ToT) framework developed by Berthon and colleagues to explore the disparate paths that AI has taken and will take in the coming years, especially in the form of chatbots. This framework provides managers with a conceptual tool to strategically plan for the enormous promises and perils of AI in general and of chatbots specifically.