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(2013). Modelling real-time online information needs: A new research approach for complex consumer behaviour. Journal of Marketing Management,, 950-972. Modelling real-time online information needs: A new research approach for complex consumer behaviour AbstractA major challenge for online vendor website operations is serving information that meets visitor needs at a given point in their purchase process. The problem arises from the complexity of human behaviour as well as changing needs with the evolution of consumer knowledge and skills through the purchase process. The most difficult element however is determining the effects of information provided on the site as well as from other sources that the consumer may access and anticipating resulting consumer needs. This paper discusses the contributions and limitations of current modelling techniques and utility studies of online consumer information to model consumer needs in real time. An alternative basis for real time customer need appraisal is proposed using clickstream and customer input data combined with online information utility to enable more effective information serving. This requires further academic research and changes in practitioner online marketing operations. ABSTRACTA major challenge for online vendor website operations is serving information that meets visitor needs at a given point in their purchase process. The problem arises from the complexity of human behaviour as well as changing needs with the evolution of consumer knowledge and skills through the purchase process. The most difficult element however is determining the effects of information provided on the site as well as from other sources that the consumer may access and anticipating resulting consumer needs. This paper discusses the contributions and limitations of current modelling techniques and utility studies of online consumer information to model consumer needs in real time. An alternative basis for real time customer need appraisal is proposed using clickstream and customer input data combined with online information utility to enable more effective information serving. This requires further academic research and changes in practitioner online marketing operations.

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This paper describes the work carried out at NOV Downhole on an in house designed and built, small scale, vibration test rig which was developed with the purpose of studying the effect of axial excitation on tubular retrieval. There are currently well established downhole tools that aid tubular retrieval by way of introducing axial excitation into the drill string fish- with resulting reductions in overpull requirements. The mechanism for overpull reduction during axial excitation is by way of effectively fluidizing the media surrounding the tubulars and thereby reducing the frictional forces holding them. By exciting drill string resonances of the fish during the axial excitation process, it is possible for the tubular retrieval fish to behave as a dynamic vibration absorber – a characteristic of which is to increase its response amplitude. This will effectively enhance the fluidizing process. During the rig testing, it has been possible to compare the Axial Excitation Tool performance at drill string fish resonance frequency with other frequencies. The rig tests demonstrate significant increase in fish response amplitude with the Axial Excitation Tool present at the resonance frequency. Full scale field operations where an Axial Excitation Tool technology has been applied have resulted in significant overall reductions in overpull. During the field tests, axial excitation tool and tubular retrieval fish response was intended to be measured and recorded using the black box system. However, this has yet to be achieved, but still remains a future objective. Never the less, the results for the cased studied so far have validated the rig tests and mathematical modelling. With reference to offset data, the paper presents actual field data that demonstrates significant reductions in time spent during tubular retrievals, and the corresponding cost savings.