Dansk

Use of Big Textual Data can strengthen intelligent transport in Denmark

Nyheder

Big textual data is still an untapped source of big data that holds great potential for supporting intelligent logistics and transportation operations.

 
Photo: Scanpix/Iris/Best-Backgrounds
12/06/2017
 
Over the past few years, there has been an increased focus on intelligent transport by creating smart, green and integrated transportation systems for the future, both at the European level but also at the national level. In Denmark, Copenhagen Commune has earmarked DKK 60 Million towards intelligent transport systems between the years 2014 - 2018. One of its initiatives, Copenhagen Intelligent Transport System (CITS), uses big data on user coordinates to understand user behaviour, and thereby support intelligent transport. 
 
But beyond such Internet of Things, and sensor generated geo-location data, Big “Textual” Data is also a useful intelligent data source for user opinions and preferences. Textual data from sources such as Twitter, Facebook, Google maps, blogs, Trustpilot, newspaper articles etc. can be classified as big textual data. It is still an untapped source of big data that holds great potential for supporting intelligent logistics and transportation operations.
 
This was one of the conclusions of a workshop organized by researchers at the Dept. of Operations Management at CBS organised an intensive workshop for the Danish logistics and transportation sector, in order to explore the potential of textual data and text analytics in Denmark. The seminar regrouped several executives from leading Danish organisations such as Maersk, Dansk Erhverv, Dansk Industri, Vejdirektorat, Movia, Coop etc 
 

Potential and obstacles in big textual data

The workshop also identified a series of barriers associated with the most important Textual Data sources. Almost half of the applications concerned social media data while the second major ones were internal sources, and finally traditional media such as newspapers. Social media was identified to be the most interesting medium alongside internal data. However, there are still a substantial number of barriers associated with the exploitation of these sources, organizational maturity being the largest one. And while social media was considered to have the highest potential, it was also considered quite problematic to implement in Denmark due to the lack of data volume and accessibility concerns. Overall though, the potential and efficiency generated by big textual data were confirmed by the workshop participants. 
 
Going forward, the exploitation of big data sources such as social and public media and the implementation of text analytics can substantially improve the intelligence and performance of the Danish transportation system. Utilizing big textual data is a formidable opportunity to understand the user’s, consumer’s and public’s opinion about transportation systems. The possibility of doing this in real time and at low costs makes it even more attractive, and it is an innovative way to extract additional value from the planned intelligent transport system initiatives.  
 
The implications for policy making would be to alleviate these challenges by supporting the further development of domain specific text analytic methods and technologies for logistics and transportation. In addition, policymakers should focus on creating conditions that make it possible to access and share publicly and privately owned textual data about user preferences and opinions.

 

FACTBOX: Big textual data - potential and barriers

Main applications:

1) Understanding user/customer opinion, e.g. tracking of real-time user satisfaction and understanding the causes behind customer complaints.
2) Improving internal operations
3) Detecting trends
4) Brand management
5) Tracking traffic conditions, e.g. understanding of behavioural responses to events on highways and thereby targeting increased safety on the Danish road network. 

 

Barriers:

1) Organizational maturity was a challenge to implement textual data analytics.
2) Data representativeness 
3) Data accessibility
4) Lack of data volume
 
 

About CBS TransText:

CBS TransText explores the novel field of Big Textual Data and the implications of its utilisation in the transport field. The aim of the workshop was to explore the potential s and barriers in the exploitation of Big textual data, how it can be applied to solve the problems faced by the actors in Danish transportation sector, and how it can aid in increasing the overall efficiency and productivity of the Danish transportation system of the future. For more information, please contact Associate Professor Aseem Kinra at the Department of Operations Management at aki.om@cbs.dk 
 
The CBS TransText project is supported by CBS Competitiveness Platform
 
Sidst opdateret: Competitiveness platform // 01/09/2017