The Industry 4.0 (I4.0) concept is concerned with the fourth industrial revolution in manufacturing, in which technological trends such as digitalization, automation and artificial intelligence are transforming production processes. Since the concept’s introduction at the Hannover Fair in Germany in 2011, I4.0 has enjoyed a meteoric rise in popularity and is currently high on the agenda of governments, politicians and business elites. In light of these observations, some commentators have asked the question of whether I4.0 is a concept that is hyped up and possibly just the latest in a long line of fashionable management concepts introduced over the course of the last few decades. Therefore, the aim of this paper is to provide a critical outside-in look at the emergence and rise of I4.0. Theoretically, these processes are viewed through the lens of management fashion, a theoretical perspective well suited to examinations of evolutionary trajectories of management concepts and ideas. The findings indicate that the I4.0 concept has quickly become highly popular and is dominating much of the popular management discourse. The concept has migrated out of the specialized manufacturing discourse to become a more general concept with mainstream appeal and applicability, evidenced by a multitude of neologisms such as Work 4.0 and Innovation 4.0. The numbers 4.0 have spread in a meme-like fashion, evidenced by the fact that the combination of a noun and the numbers 4.0 are used to signal and usher in discussions about the future of business and society. While there is much evidence that clearly shows that the concept has had a wide-ranging impact at the discursive level, the currently available research is less clear about what impact the concept has had so far on industries and organizations worldwide.

The Balanced Scorecard (BSC) is a one of the most popular and contagious management ideas of our time. In previous research the diffusion and institutionalization of the BSC has been viewed through different theoretical lenses, most notably the management fashion perspective. Recently the virus perspective has been introduced as an alternative theory of how management ideas spread, but so far no study has applied this theory in the context of the BSC. In this paper we show that the fashion and virus perspectives provide complementary insights into the diffusion and institutionalization of the BSC. The fashion perspective is particularly well suited for explaining the infectiousness of the BSC and the ways in which organizations are exposed to the BSC idea. The virus theory can better explain how the BSC idea is implemented as a practice in organizations, and the different trajectories that the BSC idea may take in different contexts. A combination of these two perspectives provides a fuller picture of the diffusion and institutionalization of the BSC.

The diffusion of fashionable management concepts is an important research topic in management and organization studies. Researchers have pointed out that various actors such as consultants, conference organizers and the business media comprise the so-called "management fashion arena" around a management concept. However, a weakness of extant conceptualizations of management fashion arenas is in the lack of an explicit consideration of the dynamics between local and international actors. Drawing on the notion of "institutional duality", we argue that the concept's trajectory at the national level is shaped by both country-specific actors and international actors. Furthermore, we recognize that the presence and involvement of different types of actors may vary across different countries. Empirically, we analyze the level of involvement of actors such as consultants, professional groups, software firms, and conference organizers in the cross-national diffusion of the Balanced Scorecard (BSC) in the three Scandinavian countries. The comparative analysis of the data shows both similarities and differences between the three countries in terms of which actors have been the most influential players. Despite certain similarities and overlaps, the three markets can be considered largely national with key local players. Furthermore, country-specific actors appear to have played a particularly important role in the early phase in terms of establishing the concept in the local markets. These findings are used to elaborate on present conceptualizations of the management fashion arena, and to discuss the role of local and international actors in the cross-national diffusion of management concepts.

This paper aims to discuss the current state of Google Trends as a useful tool for fashion consumer analytics, show the importance of being able to forecast fashion consumer trends and then presents a univariate forecast evaluation of fashion consumer Google Trends to motivate more academic research in this subject area. Using Burberry—a British luxury fashion house—as an example, we compare several parametric and nonparametric forecasting techniques to determine the best univariate forecasting model for “Burberry” Google Trends. In addition, we also introduce singular spectrum analysis as a useful tool for denoising fashion consumer Google Trends and apply a recently developed hybrid neural network model to generate forecasts. Our initial results indicate that there is no single univariate model (out of ARIMA, exponential smoothing, TBATS, and neural network autoregression) that can provide the best forecast of fashion consumer Google Trends for Burberry across all horizons. In fact, we find neural network autoregression (NNAR) to be the worst contender. We then seek to improve the accuracy of NNAR forecasts for fashion consumer Google Trends via the introduction of singular spectrum analysis for noise reduction in fashion data. The hybrid neural network model (Denoised NNAR) succeeds in outperforming all competing models across all horizons, with a majority of statistically significant outcomes at providing the best forecast for Burberry’s highly seasonal fashion consumer Google Trends. In an era of big data, we show the usefulness of Google Trends, denoising and forecasting consumer behaviour for the fashion industry.

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