Publication database

Traditional luxury goods companies have treated digital as a channel. But they’re now starting to treat it as a marketplace in its own right, thanks largely to Blockchain technology, which has delivered the Non-Fungible Token. Today, the key ingredients of luxury – rarity, exclusivity, and cost — can also apply to virtual products, as companies like Balenciaga, Louis Vuitton, and Gucci have realized.

Alexander and Lorenzo were at a crossroads with their biotech startup, PhagoMed. They had left high-profile positions at Boston Consulting Group (BCG) three years earlier, driven by a bold vision to tackle the global crisis of antibiotic resistance using phages, viruses with the remarkable ability to target specific bacteria. Despite a robust commitment to R&D yielding deeper insights into phage biology, the journey from lab to clinic was frustratingly slow. And with their capital dwindling, they faced the urgent need to reassess their strategic direction and resource allocation.

While decades of research have demonstrated that networks, through their structural configurations, powerfully influence people’s behaviors, attitudes, and outcomes, recent work has sought to better understand the role of individuals in shaping network processes. There are increasing appeals to devote greater attention to the differences individuals exhibit in establishing, managing, and navigating social relations. Accumulated evidence underlines that 1) individuals may be able to actively position themselves in the network and that 2) agency and purposive action may look different for certain individuals despite occupying similar network positions. In response to these emerging discussions, our symposium aims to contribute to a better understanding of individual agency in network theory. Questions include: What role do individuals play in shaping the process of network evolution? And, how do these dynamics impact the distribution of social capital (positive or negative) among actors within networks? This line of work provides a promising starting point for network agency research. Our presenters’ research highlights that a productive conceptualization of individual agency within organizational networks should be multifaceted. People might strategically leverage social relations and network relations for their own sake without meaningfully changing the structure of their networks. They can also take actions that meaningfully shape the architecture of their networks, intentionally or otherwise. During the processes of individuals exerting agency in shaping their social relations and exploiting network-related advantages, numerous potential mechanisms exist and should be systematically elaborated.

With permission of the Academy of Management

Artificial intelligence (AI) is diffusing rapidly throughout the economy, raising questions regarding its impact on human workers. Current theories predict that the degree to which humans are replaced (automation) or supported (augmentation) will depend on characteristics of the task such as its degree of routinization and manual vs. cognitive nature. Yet, existing empirical evidence tends to come from aggregate occupation data or individual case studies, with limited research using larger samples of projects or tasks. Moreover, whether and how AI is implemented may not only depend on task characteristics but also on managers’ objectives, which may go beyond narrow efficiency to include benefits resulting from human employment itself (“employment goals”). We provide novel empirical evidence using data from more than 1,200 research projects that involve crowd members in different tasks such as data collection, data analysis, or creative problem solving. We confirm that the use of AI is associated with task characteristics, although the patterns are more nuanced than those shown in work on prior automation technologies such as computers and robots. Moreover, we find that managers pursuing employment goals are less likely to use AI for automation, while they are just as likely as others to use AI to augment the work of human workers. We contribute to the literature on AI adoption in organizations by providing rare evidence from project-level data, and by highlighting that the path towards “good AI” or “bad AI” is, partly, a matter of human choice.

With permission of the Academy of Management