Innovation and Technology Management

A research group of the Business School.

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The Centre of Innovation and Technology Management (CITM) is a multidisciplinary research centre that aims to develop and disseminate knowledge in the area of operations, technology and innovation management.

Our research, which uses rigorous methods and is published in some of the leading journals, explores themes inspired by managerial challenges and practice. The rigour and relevance of our research is demonstrated by the impact our research is having on companies, public sector organizations, industry associations, professional bodies and government, as well as the everyday lives of individuals.

How we work

We operate in an outward looking environment by proactively and systematically engaging with external stakeholders including businesses, other Universities, funding bodies, and professional associations.

The structure and operation of the centre is based around research based themes. Although the themes are not exclusive, the activities organised by the centre are aligned with each theme. This bottom-up approach enables the centre’s researchers to combine their skills and expertise to address research questions and challenges which are current relevant, and have impact.

Three research themes

Open Innovation

Projects explore the sharing of knowledge and ideas across the supply chain. During our first year we have launched a MOOC on Open Innovation and organised an Innovation Colloquium.

Disruptive Innovation and Data Analytics

Projects associated with this theme aim to provide the platform for proof testing ideas that can disrupt the business models of our key stakeholders, e.g. on the provision of solutions to daily jobs as opposed to selling of products, and the impact of Industry 4.0.

Measuring the impact of Innovation (Innovation Observatory)

The aim of the innovation observatory is to work with local Universities for supporting business innovation. It is within its scope to measure and evaluate levels of innovation across sectors.

Staff

Faculty Administration & Operations, Durham University Business School, Mill Hill Lane, Durham DH1 3LB

• Professor Susan Hart

Department of Management and Marketing, Durham University Business School, Mill Hill Lane, Durham, DH1 3LB

• Professor Christos Tsinopoulos

Faculty, Durham University Business School, Mill Hill Lane, Durham DH1 3LB

• Dr Roberta Aguzzoli
• Dr Mauro Bambi
• Dr Atanu Chaudhuri
• Dr Li Ding
• Professor Kiran Fernandes
• Dr Çağrı Haksoz
• Professor Sascha Kraus
• Dr Zach W. Y. Lee
• Dr Jorge Lengler
• Dr Riccardo Mogre
• Professor Tyrone Pitsis
• Dr Paulo Savaget
• Dr Stephanie Scott
• Dr Manish Shukla
• Professor Carlos M.P. Sousa
• Dr Dylan Sutherland
• Dr Sarah Xiao
• Dr Ji (Karena) Yan

Uncategorised

• Dr Alan Jessop

Publications by staff in this group

Journal Article

• Hughes, M., Hughes, P., Yan, J. & Sousa, C.M.P. (2019). Marketing as an Investment in Shareholder Value. British Journal of Management 30(4): 943-965.
• Harris, R. & Yan, J. (2019). The Measurement of Absorptive Capacity from an Economics Perspective: Definition, Measurement and Importance. Journal of Economic Surveys 33(3): 729-756.
• Tsinopoulos, C., Sousa, C. & Yan, J. (2018). Process Innovation: Open innovation and the moderating role of the motivation to achieve legitimacy. Journal of Product Innovation Management 35(1): 27-48.
• Geary, J., Aguzzoli, R. & Lengler, J. (2017). The Transfer of ‘International Best Practice’ in a Brazilian MNC: A Consideration of the Convergence and Contingency Perspectives. Journal of International Management 23(2): 194-207.
• Obeidat, Z.M.I., Xiao, Sarah, Iyer, G.R. & Nicholson, M. (2017). Consumer Revenge Using the Internet and Social Media: An Examination of the Role of Service Failure Types and Cognitive Appraisal Processes. Psychology & Marketing 34(4): 496-515.
• Nucciarelli, A., Li, F., Fernandes, K., Goumagias, N., Cabras, I., Devlin, S., Kudenko, D. & Cowling, P. (2017). From value chains to technological platforms: The effects of crowdfunding in the digital game industry. Journal of Business Research 78: 341-352.
• Zhu, A., von Zedtwitz, M., Assimakopoulos, D. & Fernandes, K. (2016). The impact of organizational culture on Concurrent Engineering, Design-for-Safety, and product safety performance. International Journal of Production Economics 176: 69-81.
• Mogre, R., Talluri, S. & D’Amico, F. (2016). A decision framework to mitigate supply chain risks: an application in the offshore-wind industry. IEEE Transactions on Engineering Management 63(3): 316-325.
• Huang, S., Chen, J., Wang, Y., Ning, L., Sutherland, D., Zhou, Z. & Zhou, Y. (2015). External heterogeneity and its impact on open innovation performance. Technology Analysis & Strategic Management 27(2): 182-197.
• Tsinopoulos, C. & Mena, C. (2015). Supply chain integration configurations: Process structure and product newness. International Journal of Operations and Production Management 35(10): 1437-1459.
• Milewski, S., Fernandes, K. & Mount, M. (2015). Exploring technological process innovation from a lifecycle perspective. International journal of operations and production management 35(9): 1312-1331.
• Iyer, G.R., Xiao, S., Sharma, A. & Nicholson, M. (2015). Behavioral issues in price setting in business-to-business marketing: a framework for analysis. Industrial marketing management 47: 6-16.
• Tan, Q. & Sousa, C. M. P. (2015). Leveraging Marketing Capabilities into Competitive Advantage and Export Performance. International Marketing Review 32(1): 78-102.
• Wang, Y., Sutherland, D., Ning, L. & Pan, X. (2015). The evolving nature of China's regional innovation systems: Insights from an exploration–exploitation approach. Technological Forecasting and Social Change 100: 140-152.
• Sousa, C.M.P., Lengler, J. & Martínez-López, F.J. (2014). Testing for Linear and Quadratic Effects between Price Adaptation and Export Performance: The Impact of Values and Perceptions. Journal of Small Business Management 52(3): 501-520.
• Okike, C., Fernandes, K. & Xiong, Y. (2014). Impact of operator experience on information feedback and reusability. Production Planning & Control: The Management of Operations 25(4): 318-331.
• Shi, L. & Fernandes, K. (2014). A diffusion model for service products. Journal of service marketing 28(4): 331-341.
• Shi, L. & Fernandes, K. (2014). Exploring the Role of Innovativeness and Opinion Leadership in Diffusion. International Journal of Innovation Management 18(4): 1450029.
• Shi, L., Fernandes, K. & Chumnumpan, P. (2014). Diffusion of multi-generational high-technology products. Technovation 34(3): 162-176.
• Tsinopoulos, C., Lages, L.F. & Sousa, C.M.P. (2014). Export experience counts: Exploring its effect on product design change. R&D Management 44(5): 450-465.
• Shukla, M. & Jharkharia, S. (2014). Harvest scheduling to reduce waste in agri-fresh produce supply chains: An Artificial Immune System-based solution approach. International Journal of Planning and Scheduling 2(1): 14.
• Mogre, R., Wong, C.Y. & Lalwani, C.S. (2014). Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information. International Journal of Production Research 52(17): 5223-5235.
• Micheli, G., Mogre, R. & Perego, A. (2014). How to choose mitigation measures for supply chain risks. International Journal of Production Research 52(1): 117-129.
• Al Zu’bi, Z. & Tsinopoulos, C. (2013). An outsourcing model for lead users: An empirical investigation. Production Planning and Control 24(4-5): 337-346.
• Ding, L. & Mahbubani, J. (2013). A two-stage decision model of vertical integration. Management Decision 51(2): 306-320.
• Ding, L. & Glazerbrook, K.D. (2013). Dynamic routing in distinguishable parallel queues: an application of product returns for remanufacturing. OR Spectrum 35(3): 585-608
• Grody A., Fernandes, K., Hughes, P. & Toms, J. (2013). The Basel Committee’s fundamental review of the trading book: A commentary. Journal of Risk Management in Financial Institutions 1(6-9).
• Shukla, N., Choudhary, A., Prakash, P., Fernandes, K. & Tiwari, M. (2013). Algorithm Portfolios for Logistics Optimization Considering Stochastic Demands and Mobility allowance. International Journal of Production Economics 141(1): 146-166.
• Agrawal, T., Sao, A., Fernandes, K., Tiwari, M. & Kim, D. (2013). A Hybrid Model of Component Sharing and Platform Modularity for Optimal Product Family Design. International Journal of Production Research 51(2): 614-625.
• Liao, N., Fernandes, K., Downs, D. & Foley, G. (2013). Facilitating the Adoption of Open Source Technologies for UK Health Care: An Ecosystem Framework. International Journal of Health Information Management Research 1(1): 37-47.
• Tsinopoulos, C. & Al Zu’bi, Z. B. M. F. (2013). Lead users, suppliers, and experts: the exploration and exploitation trade-off in product development. International Journal of Technology Marketing 9(1): 6-20.
• Tsinopoulos, C. & Al Zu’bi, Z. (2012). Suppliers versus Lead Users: Examining their Relative Impact on Product Variety. Journal of Product Innovation Management 29(4): 667-680.
• Jessop, A. (2012). A decision aid for finding performance groups. Benchmarking: An International Journal 19(3): 325-339.
• Fernandes, K. (2012). A Framework for Service Systems Analysis: Theory and Practice. Production Planning & Control: The Management of Operations 23(7): 480-497.
• Okike, C. & Fernandes, K. (2012). Impact of Information Use Architecture on Load and Usability. Information Processing and Management 48(5): 995-1016.
• Xiong, Y., Yan, W., Fernandes, K., Zhongkai, X. & Guo, N. (2012). Bricks Vs Clicks: The Impact of Manufacturer Encroachment with a Dealer Leasing and Selling of Durable Goods. European Journal of Operational Research 217(1): 75-83.
• Jha, A., Somani, K., Tiwari, M., Chan, F. & Fernandes, K. (2012). Minimizing transportation cost of a joint inventory location model using modified adaptive differential evolution algorithm. The International Journal of Advanced Manufacturing Technology 60(1-4): 329-341.
• Evangelista, P., Mogre, R., Perego, A., Raspagliesi, A. & Sweeney, E. (2012). A survey based analysis of IT adoption and 3PLs' performance. Supply Chain Management 17(2): 172-186.
• Jessop, A. (2011). Using imprecise estimates for weights. Journal of the Operational Research Society 62(6): 1048-1055.
• Paige, R., Drivalos, N., Kolovos, D., Fernandes, K., Power, C., Olsen, G. & Zschaler, S. (2011). Rigorous identification and encoding of trace-links in model-driven engineering. Software & Systems Modeling 10(4): 469-487.
• Argon, N.T., Ding, L., Glazebrook, K.D. & Ziya, S. (2009). Dynamic routing of customers with general delay costs in a multiserver queuing system. Probability in the Engineering and Informational Sciences 23(2): 175-203.