Business Analytics for the Management of Information Systems Development
Special issue call for papers from Information Technology & People
Submission deadline: 30th September 2020
Special issue editors:
Denis Dennehy, National University of Ireland Galway, Ireland
Email: [email protected]
Ilias Pappas, University of Agder, Norway
Email: [email protected]
Samuel Fossa Wamba, Toulouse Business School, France
Email: [email protected]
Katina Michael, Arizona State University, USA
Email: [email protected]
Overview of Special Issue
Information Systems Development (ISD) has been part of the intellectual core of information systems for over 40 years (Obrand et al., 2018; Sidorova et al., 2008). Its chequered history of successes and failures has, however, been an ongoing concern of the IS research community (Dwivedi et al., 2015; Hassan & Mathiassen, 2017). Despite efforts to improve the management of ISD projects, these efforts have not had the desired effect (Lim et al., 2011).
There is anecdotal evidence that business analytics can help project managers to (i) understand the dynamics and collective state of complex projects, (ii) detect and forecast trends, (iii) improve the effectiveness of risk models, (iv) evaluate the effectiveness of a change to the development process, and (v) distinguish questions of ‘information’ from questions of ‘insight’ (Davenport et al., 2010).
Business analytics are frequently referred to as ‘the techniques, technologies, systems, practices, methodologies, and applications that analyse critical business data to help an enterprise better understand its business and market and make timely decisions’ (Chen et al., 2012, p.1166). Yet, much of the research conducted to date has focused on the technologies of business analytics and not enough on the people and their organisational context in which such technologies are intended to be used (Abbasi et al, 2017; Conboy et al., 2018; Mikalef et al., 2019). This is a significant limitation given that the ISD environment is a highly metric oriented, complex, and socially embedded activity that is continuously changing (Conboy, 2009; Kudaravalli et al., 2017; Windeler et al., 2017).
This special issue seeks to collect contemporary research on the latest developments and challenges of how organisations exploit business analytics to support project/portfolio managers, project teams, and other project stakeholders.
Indicative List of Anticipated Themes
This special issue seeks a wide range of articles that draw on diverse project settings, theories, and approaches to understand the different aspects of business analytics as applied to the context of ISD. The following questions are of interest for the special issue:
• How can business analytics be used to better understand and manage ISD projects?
• What value does business analytics provide to ISD management and development teams?
• What tensions arise from the integration of business analytics with traditional and agile methods and practices?
• What are the emerging best practices that enable business analytics to be embedded within the ISD process and the wider organisation?
• Does the deployment of business analytics make existing agile methods and practices less valuable or even obsolete?
• What new metrics and standards can business analytics provide to manage and control ISD projects more effectively?
• How can business analytics enable organisational learning and innovation in the context of ISD?
• How are business analytics being applied in various types (distributed, large scale) of ISD projects?
• How can business analytics support the scaling of ISD projects?
• What are the change management and organisational cultural issues that need to be considered when developing analytical capabilities?
• How can business analytics provide new ways of working in ISD projects?
• What ethical issues stem from the use of business analytics in ISD projects?
• How can business analytics be used to support more effective decision making?
• What are the new theories and theoretical developments to explain the implementation and use of business analytics in ISD projects?
These questions are not intended to be exhaustive. Rather they are intended to stimulate thinking about the role of business analytics in the management of ISD projects across various levels of analysis - from participants in individual projects through projects, programs, portfolios, organisations, and the wider society. We welcome submissions that address questions pertaining to all aspects of the intersection of business analytics and ISD project management.
Paper Development Workshop (ECIS 2020)
• Submission of extended abstracts commences 1st February 2020 and ends midnight (CET) 31st March 2020
• Authors will be notified of decision by mid-April 2020
• Paper Development Workshop: 14th June 2020
Information Technology & People Special Issue:
• Initial paper submission deadline: 30th September, 2020
• First round authors notification: 30th November, 2020
• Invited revisions deadline: 31st January, 2021
• Second round authors notification: 31st March, 2021
• Final revision deadline: 31st May, 2021
• Final authors notification: 30th June, 2021
• Projected publication date: Winter 2021
Paper Development Workshop
Only invited authors can attend this workshop. Authors will have the opportunity to present their extended abstracts and receive feedback on how best to develop their article for submission to the special issue with Information Technology & People.
Extended abstracts (1,500 - 3,000 words) must use the ECIS 2020 (completed research) paper template. This word limit does not include references, tables, or figures. There is no specific structure but the extended abstract must address the following:
• What is the theoretical lens of your research and how does this theory help us to better understand the nature of the research phenomenon?
• What are the specific contributions that your research will make to academia and practice?
• What are the intended implications of your research for academia and practice?
We welcome studies using the range of investigative methodologies qualitative and quantitative, case study, with data collected by survey, interview, observation, analytic analysis. Technical papers and systematic literature reviews are not within the scope of this special issue. If you have any further questions, please consult any of the guest editors.
Submission of extended abstracts in PDF format is via EasyChair (https://easychair.org/). Submission of full papers in PDF format is via Manuscript Central (http://mc.manuscriptcentral.com/itp). While there is no guarantee that work presented at the workshop will be published in the special issue, it is expected that some will eventually be published in Information Technology & People, once further developed. It is possible to submit a full paper without having submitted an extended abstract but we advise submitting an extended abstract.
To view the author guidelines for this journal, please visit: https://www.emeraldgrouppublishing.com/products/journals/author_guidelines.htm?id=itp
Please submit your manuscript via our review website: http://mc.manuscriptcentral.com/itp
Abbasi, A., Sarker, S. and Chiang, R.H., 2016. Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17(2), p.I.
Conboy, K., Dennehy, D., & O'Connor, M. (2018). ‘Big time’: An examination of temporal complexity and business value in analytics. Information & Management.
Conboy, K., 2009. Agility from first principles: Reconstructing the concept of agility in information systems development. Information Systems Research, 20(3), pp.329-354.
Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4).
Davenport, T.H., Harris, J. and Shapiro, J., 2010. Competing on talent analytics. Harvard Business Review, 88(10), pp.52-58.
Dwivedi, Y.K., Wastell, D., Laumer, S., Henriksen, H.Z., Myers, M.D., Bunker, D., Elbanna, A., Ravishankar, M.N. and Srivastava, S.C., 2015. Research on information systems failures and successes: Status update and future directions. Information Systems Frontiers, 17(1), pp.143-157.
Hassan, N.R. and Mathiassen, L., 2018. Distilling a body of knowledge for information systems development. Information Systems Journal, 28(1), pp.175-226.
Kudaravalli, S., Faraj, S. and Johnson, S.L., 2017. A Configural Approach to Coordinating Expertise in Software Development Teams. MIS Quarterly, 41(1).
Lim, E.P., Chen, H. and Chen, G., 2013. Business intelligence and analytics: Research directions. ACM Transactions on Management Information Systems (TMIS), 3(4), p.17.
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: the mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272-298.
Sidorova, A., Evangelopoulos, N., Valacich, J.S. and Ramakrishnan, T., 2008. Uncovering the intellectual core of the information systems discipline. MIS Quarterly, pp.467-482.
Öbrand, L., Augustsson, N.P., Mathiassen, L. and Holmström, J., 2019. The interstitiality of IT risk: An inquiry into information systems development practices. Information Systems Journal, 29(1), pp.97-118.
Windeler, J.B., Maruping, L. and Venkatesh, V., 2017. Technical systems development risk factors: The role of empowering leadership in lowering developers’ stress. Information Systems Research, 28(4), pp.775-796.