Funded PhD Opportunities

Technological innovation in the retailing sector: A study of emerging technologies and systems of innovation

  • Application end date: 11th February 2018
  • Funding Availability: Funded PhD project (EU/UK/International)
  • Department: Strategy, Enterprise and Innovation
  • PhD Supervisor: Dr. Chris Simms, Dr. Sercan Ozcan.

Project code: BUSM3910218

Project description

Understanding current key technologies and forecasting emerging technologies expected to be of greatest significance is critical across all industries. This PhD project examines current technologies, systems of innovation and projects future technologies within the UK retailing sector. This sector is experiencing a challenging period, with high levels of competition, low profit margins, labour intensive operations and shifting consumer shopping habits. Thus innovative technological solutions are required to increase the efficiency of retailer operations, such as automated or semi-automated processes, technologies that minimise labour-intensive activities, and innovations that increase the efficiency of core operations (Van Beuningen et al., 2009). Technological advances are also providing opportunities for retailers to develop new and improved services (Vargo et al., 2017). Indeed, large retailers, such as Tesco, Wall-mart and Amazon, have been heavily investing in technologies such as robotics, internet of things (IOT) and advanced payment methods, in order to gain a competitive edge (Dekimpe et al., 2011). In recent years the industry has been characterised by a high level of change through the growth of self-checkout and scanning technologies, online shopping, digital displays, customer information databases (e.g. loyalty cards), and the growing use of automated ‘dark stores’. Retailers have also been utilising new technologies to enhance their service offering and provide additional customer value through improved interactions at each point in the multichannel retailing environment (Bowen and Schneider 2014). This has resulted in the proliferation of new technologies. 

Considering the growing significance of technologies, associated investments and R&D activities amongst the retailers, it is crucial to examine current and future technological innovations that are expected to change the way retail operations will occur in the future. Further, there is a need to uncover the key actors within the innovation system that are involved in bringing new technologies into the market. The PhD candidate will explore and select an appropriate data collection method to achieve the project aims. A number of methods to understand current and emerging technologies are available. This includes either qualitative methods, such as interviews, case studies, or the Delphi method. Or the student can adopt a scentometrics and social network analysis approach utilising text mining/big data analysis of large patent and publication databases (see Ozcan and Islam, 2017). Utilising the selected data collection method (additional training available where required), the student will analyse current technologies and forecast future technologies within the retailing sector. In doing so they will uncover key opportunities, critical technologies, and those with most innovation potential. Hence the key aims of the project are to:

  • Explore the trends in retailing activities 

  • Identify promising retail technologies that can impact the industry

  • Understand diffusion of existing and new retailing technologies, enabling forecasting

  • To analyse retail sector innovation network and innovation system

Supervisor Profiles

Dr. Chris Simms, Reader in Innovation Management and New Product Development.

Dr. Sercan Ozcan, Senior Lecturer in the Strategy, Enterprise and Innovation Subject Group.

Admissions criteria

You’ll need a good first degree from an internationally recognised university (depending upon chosen course, minimum second class or equivalent) or a Master’s degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Candidate specific requirements

  • Experience of quantitative data analysis

  • Preferably experience of text mining or network analysis

  • Preferably experience in text mining or technology and bibliometric analysis

Enquiries

Informal enquiries are encouraged and can be made to Dr Chris Simms at chris.simms@port.ac.uk or Dr Ozcan at sercan.ozcan@port.ac.uk.

For administrative and admissions enquiries please contact balresearchdegrees@port.ac.uk.

How to Apply

You can apply online at www.port.ac.uk/applyonline. You are required to create an account which gives you the flexibility to save the form, log out and return to it at any time convenient to you.

A link to the online application form and comprehensive guidance notes can be found at www.port.ac.uk/pgapply.

When applying, please quote project code: BUSM3910218.

Interview date: TBC.

Start date: October 2018.

Applications should include

  • a full CV including personal details, qualifications, educational history and, where applicable, any employment or other experience relevant to the application

  • contact details for two referees able to comment on your academic performance

  • a research proposal of 1,000 words outlining the main features of a research design you would propose to meet the stated objectives, identifying the challenges this project might present and discussing how the work will build on or challenge existing research in the above field.

  • proof of English language proficiency (for EU and international students)

All the above must be submitted by the 11th of February 2018. 

Funding notes

UK/EU students -  The fully-funded, full-time three-year studentship provides a stipend that is in line with that offered by Research Councils UK of £14,553 per annum.

International students - International students applying for this project are eligible to be considered for the Portsmouth Global PhD scholarships.

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