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Low productivity in construction is typically blamed on the seemingly complex and chaotic nature of construction, which emerges as the stakeholders do not have an adequate picture of the evolving situation. The ever-increasing volume of situation data owing to the recent advances in IoT devices and reality capture platforms provide a unique opportunity to capture the actual situation data of construction projects accurately at a fraction of the cost compared to manual status tracking and reporting. This paper aims to investigate the concept of a situation picture, challenges in collecting situation data and its benefits.

Empirical data is collected through interviews in California and Finland, and by organizing workshops.

We contribute to literature on managing operational information by defining the concept of a situation picture in the context of construction, specifically from the blue-collar’s perspective during on-site activities. We present the key components of a conceptual information model that represents a situation picture in construction.

The applicability of conceptual information model of situation picture is not tested in practice, but the model will provide a starting point for research to comprehensively integrate social and digital information exchange for improving workflow.

The paper claims that designing and building comprehensive information management infrastructure would contribute to solving the problems of low productivity, quality and safety in construction projects.

Research on situation picture and situation awareness is scarce in the context of construction. The study links various information management technologies and practices to actual construction productivity.

Over the past 50 years, a substantial interest has been put to research on how innovation spreads within social networks over time (see Rogers, 1962, 2010). Our initial aim was to examine innovation diffusion in industrial networks. We operationalized the research through a case study of an advertising network by using systematic combining as the approach (Dubois & Gadde, 2002, 2014). From the initial focus of innovation diffusion, the rematching of data and theory led us to focus on the barriers of innovation diffusion. By doing so, we found out that multilevel strategizing appears to be an important phenomenon in understanding dynamics of innovation diffusion within industrial networks. Specifically, strategizing occurs in two levels: (1) the groups within the network compete for position, and (2) actors within a group compete for position by trying to differentiate themselves from other group actors. A strategic mismatch between the two levels leads the network to become decelerated or even static in diffusing new innovations (Abrahamsen, Henneberg, & Naudè, 2012). Uncovering these findings would not have been possible without the use of systematic combining and the constant matching between theoretical and empirical domains.

The term “fashion” triggers images of frivolous symbolic production with a particular impact on women, quite a world apart at first sight from high technology and mobile telephony that traditionally tend to be associated with science, rationality and masculinity. Surprisingly, we show in this paper that the field of mobile telephony has, for a number of years now, been impacted and significantly transformed by the transposition of fashion logics. We deconstruct the process of logic transposition, considering key moments and key actors, key modes and mechanisms. The comparison of multiple case studies within the mobile telephony industry also points to the limits of transposition and to varying degrees of hybridization and logic co-habitation. This process of logic transposition is, we argue, profoundly transforming the mobile telephony industry, bringing it closer, on many counts, to “cultural industries”. In the end, we draw a number of theoretical conclusions on logic transposition as an important mechanism of institutional change.

This chapter critically examines whether it may be possible to create an AI-based authentic leader, questioning the inherent contradiction between artificial and authentic. The authors pose central research questions: Does the application of AI – even just as a powerful resource – challenge the tenets of authentic leadership? What are the possibilities and limitations of the concept of authenticity in AI-based management systems? Moreover, with the help of three vignettes illustrating practical applications of AI-based systems in leadership and management tasks, the authors illustrate how technology may be used to either control or empower workers and leaders. The authors call for research to assess whether the search for authenticity in AI-based leadership could lead anywhere, warning that it could entrap us in unresolvable existential and conceptual ambiguity, ultimately diverting our focus from the essence of leadership altogether.

We study career and wage dynamics within and between firms using a large linked employer-employee panel dataset spanning 26 years. We construct six-level hierarchies for more than 5,000 firms. We replicate most of the analyses from Baker, Gibbs, and Holmström (1994) and make some extensions. Many of our results corroborate their findings. Careers within firms are important, but the strong version of the theory of internal labor markets does not fit the data. Recent theories of career and wage dynamics explain our findings well.