A longitudinal study of the actual value of big data and analytics: The role of industry environment

2021 ◽  
Vol 60 ◽  
pp. 102389
Author(s):  
Suning Zhu ◽  
Tianxi Dong ◽  
Xin (Robert) Luo
2014 ◽  
Vol 22 (3) ◽  
pp. 270-293 ◽  
Author(s):  
Vittoria Giada Scalera ◽  
Debmalya Mukherjee ◽  
Alessandra Perri ◽  
Ram Mudambi

Purpose – The purpose of this article is to provide insights into the innovation trajectory, and knowledge pipelines of mature industry multinational enterprises (MNEs). The ability to innovate constantly amidst a turbulent and competitive environment is often the key force behind MNE survival and dominance. Design/methodology/approach – This study conducts an in-depth longitudinal study of the Goodyear Tire and Rubber Company, a global manufacturing company in the tire and rubber industry. The findings are based on USPTO patent and trademark data from 1975-2005. Findings – The analysis reveals three crucial trends: the major role of continuous investment in innovation in the firm’s survival and turnaround; the evolution of the firm’s innovation network from a headquarters-centric model toward more geographical dispersal; and the changing mix of innovation from traditional “hard” science-based research toward a greater emphasis on “softer” competencies in design and trademarks. This third trend, in particular, opens up important new avenues for research on MNE innovation practices. Originality/value – This study integrates historical analysis of a single firm in the context of its changing industry environment. The historical analysis is enriched by a detailed longitudinal quantitative analysis using a variegated dataset of patents and trademarks to investigate innovation.


Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.


2021 ◽  
Author(s):  
Claudia Chisari ◽  
Mahira Budhraja ◽  
Mani B. Monajemi ◽  
Fiona Lewis ◽  
Rona Moss‐Morris ◽  
...  

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