How Employees Experience Digital Transformation: A Dynamic And Multi-Layered Sensemaking Perspective

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

Implicit association tests:Stimuli validation from participant responses

The Implicit Association Test (IAT, Greenwald et al., J. Pers. Soc. Psychol., 74, 1998, 1464) is a popular instrument for measuring attitudes and (stereotypical) biases. Greenwald et al. (Behav. Res. Methods, 54, 2021, 1161) proposed a concrete method for validating IAT stimuli: appropriate stimuli should be familiar and easy to classify – translating to rapid (response times <800 ms) and accurate (error < 10%) participant responses. We conducted three analyses to explore the theoretical and practical utility of these proposed validation criteria. We first applied the proposed validation criteria to the data of 15 IATs that were available via Project Implicit. A bootstrap approach with 10,000 ‘experiments’ of 100 participants showed that 5.85% of stimuli were reliably valid (i.e., we are more than 95% confident that a stimulus will also be valid in a new sample of 18- to 25–year-old US participants). Most stimuli (78.44%) could not be reliably validated, indicating a less than 5% certainty in the outcome of stimulus (in)validity for a new sample of participants. We then explored how stimulus validity differs across IATs. Results show that only some stimuli are consistently (in)valid. Most stimuli show between-IAT variances, which indicate that stimulus validity differs across IAT contexts. In the final analysis, we explored the effect of stimulus type (images, nouns, names, adjectives) on stimulus validity. Stimulus type was a significant predictor of stimulus validity. Although images attain the highest stimulus validity, raw data show large differences within stimulus types. Together, the results indicate a need for revised validation criteria. We finish with practical recommendations for stimulus selection and (post-hoc) stimulus validation