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Challenges and solutions for marketing in a digital era

Leeflang, Peter S.H.; Verhoef, Peter C.; Dahlström, Peter - In: European Management Journal 32 (2014) 1, pp. 1-12

Internet usage continues to explode across the world with digital becoming an increasingly important source of competitive advantage in both B2C and B2B marketing. A great deal of attention has been focused on the tremendous opportunities digital marketing presents, with little attention on the...

Persistent link: https://www.econbiz.de/10011039708

An Extension Collaborative Innovation Model in the Context of Big Data

Li, Xingsen; Tian, Yingjie; Smarandache, Florentin; … - In: International Journal of Information Technology & … 14 (2015) 01, pp. 69-91

The processes of generating innovative solutions mostly rely on skilled experts who are usually unavailable and their outcomes have uncertainty. Computer science and information technology are changing the innovation environment and accumulating Big Data from which a lot of knowledge is to be...

Persistent link: https://www.econbiz.de/10011279047

Stay Ahead of Competition

Fok, Fok, D. - Erasmus Research Institute of Management (ERIM), … - 2013

The widespread use of the Internet and computer systems has led to a situation where data are available on almost everything. The volume and the level of detail of these data is something we considered to be impossible until a few years ago. Researchers in economics and business now have access...

Persistent link: https://www.econbiz.de/10010730462

Big Data and Specific Analysis Methods for Insurance Fraud Detection

BOLOGA, Ramona; BOLOGA, Razvan; FLOREA, Alexandra - In: Database Systems Journal 4 (2013) 4, pp. 30-39

Analytics is the future of big data because only transforming data into information gives them value and can turn data …

Persistent link: https://www.econbiz.de/10010756322

Selecting rows and columns for training support vector regression models with large retail datasets

Gür Ali, Özden; Yaman, Kübra - In: European Journal of Operational Research 226 (2013) 3, pp. 471-480

Although support vector regression models are being used successfully in various applications, the size of the business datasets with millions of observations and thousands of variables makes training them difficult, if not impossible to solve. This paper introduces the Row and Column Selection...

Persistent link: https://www.econbiz.de/10011052484

Perspectives on Big Data and Big Data Analytics

ULARU, Elena Geanina; PUICAN, Florina Camelia; APOSTU, Anca - In: Database Systems Journal 3 (2012) 4, pp. 3-14

intends to define the concept of Big Data and stress the importance of Big Data Analytics. …

Persistent link: https://www.econbiz.de/10010819177

Operational research from Taylorism to Terabytes: A research agenda for the analytics age

Mortenson, Michael J.; Doherty, Neil F.; Robinson, Stewart - In: European Journal of Operational Research 241 (2015) 3, pp. 583-595

The growing attention and prominence afforded to analytics presents a genuine challenge for the operational research … community. Many in the community have recognised this growth and sought to align themselves with analytics. For instance, the US … operational research society INFORMS now offers analytics related conferences, certification and a magazine. However, as shown in …

Persistent link: https://www.econbiz.de/10011117473

Golden Rule of Forecasting: Be conservative

Armstrong, J. Scott; Green, Kesten C.; Graefe, Andreas - Volkswirtschaftliche Fakultät, … - 2014

This paper proposes a unifying theory of forecasting in the form of a Golden Rule of Forecasting. The Golden Rule is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek all knowledge...

Persistent link: https://www.econbiz.de/10011257908

Applying analytics in the energy industry: A case study of heat rate and opacity prediction in a coal-fired power plant

Chongwatpol, Jongsawas; Phurithititanapong, Thanrawee - In: Energy 75 (2014) C, pp. 463-473

challenge, advanced analytics through data mining approaches has been applied to predict and explain the leading causes of …

Persistent link: https://www.econbiz.de/10010931401

Comparison of Three Classification Algorithms for Predicting Pm2.5 in Hong Kong Rural Area

Zhao, Yin; Hasan, Yahya Abu - In: Journal of Asian Scientific Research 3 (2013) 7, pp. 715-728

Data mining is an approach to discover knowledge from large data. Pollutant forecasting is an important problem in the environmental sciences. This paper tries to use data mining methods to forecast fine particles (PM2.5) concentration level in a new town of Hong Kong rural area. There are...

Persistent link: https://www.econbiz.de/10010883684

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