The capacity to deal with digital transformation is a valuable asset for established organizations, and employees play a crucial role in this process. This study contributes to the understanding of employees’ sensemaking of digital transformation in the tour operating industry. Using prior digital transformation research, construal-level theory (CLT), and dynamic change perspectives, our scholarly work focuses on the complexities of organizational change in a digital transformation context. Although employees generally support digital transformation, our findings show that their perceptions change over time across a range of specific challenges experienced during the employee change journey. Our findings stress the importance of adopting a social exchange lens in digital transformation knowledge as this represents deep structure change that might cause well-designed transformation processes to fail. Implications for hospitality and tourism management are discussed.
MULTIFILE
One of the main aims of game AI research is the building of challenging and believable artificial opponents that act as if capable of strategic thinking. In this paper we describe a novel mechanism that successfully endows NPCs in real-time games with strategic planning capabilities. Our approach creates adaptive behaviours that take into account long-term and short term consequences. Our approach is unique in that: (i) it is sufficiently fast to be used for hundreds of agents in real time; (ii) it is flexible in that it requires no previous knowledge of the playing field; and (iii) it allows customization of the agents in order to generate differentiated behaviours that derive from virtual personalities.
One of the main aims of game AI research is the building of challenging and believable artificial opponents that act as if capable of strategic thinking. In this paper we describe a novel mechanism that successfully endows NPCs in real-time games with strategic planning capabilities. Our approach creates adaptive behaviours that take into account long-term and short term consequences. Our approach is unique in that: (i) it is sufficiently fast to be used for hundreds of agents in real time; (ii) it is flexible in that it requires no previous knowledge of the playing field; and (iii) it allows customization of the agents in order to generate differentiated behaviours that derive from virtual personalities.
