-------- Forwarded Message -------- Subject: [WI] CfP: Special Issue in JIT on "Emerging Technologies in Information Systems Sourcing" Date: Tue, 16 Jun 2020 10:11:10 +0200 From: olik@itu.dk Reply-To: olik@itu.dk To: wi@lists.kit.edu

Call for Papers for a Special Issue of the Journal of Information Technology on: “Emerging Technologies and IS Sourcing”

Special Issue Editors: - Julia Kotlarsky, University of Auckland – New Zealand (j.kotlarsky@auckland.ac.nz, corresponding) - Ilan Oshri, University of Auckland – New Zealand - Oliver Krancher, IT University of Copenhagen – Denmark - Rajiv Sabherwal, University of Arkansas – USA

The last decade has seen a significant proliferation of new technologies. These include robotic process automation (Coombs et al. 2020; Lacity and Willcocks 2016), big data (Wiener et al. 2020), machine/deep learning and artificial intelligence (Brynjolfsson and McAfee 2016), blockchain (Du et al. 2019) and other “emerging technologies”. Consulting and market research companies have consistently predicted that the current wave of technologies will transform both front and back office operations, requiring firms to rethink their business models and strategies . While evidence suggests that firms will continue to invest in emerging technologies, there has so far been little evidence about the involvement of service providers and advisory in the selection, design and adoption of such emerging technologies.

IS sourcing research has conventionally accounted for three main areas of interest: sourcing decision, contractual structures and relationship management (Kotlarsky et al. 2020). Emerging technologies challenge these traditional conventions in the IS sourcing literature . Particular challenges include but are not limited to:

 There is greater dependency on data in emerging technologies, which triggers clients to source data science services;  The actual implementation of emerging technology often happens through platforms that involve multiple players and services;  The asset transfer model has become less relevant and yet client firms are still expected to reduce their headcount;  There is greater emphasis on the redesign of the value chain as services have become digitized and decisions are now driven by smart algorithms;  At the same time, emerging technologies are viewed as a black box, posing a skills and expertise challenge to client firms to ensure acquiring and retaining knowledge of the technology.

Further, the IS sourcing literature which has traditionally relied on three main reference theories, namely, transaction cost economics, resource dependency and social exchange (e.g., Karimi-Alaghehband et al. 2011; Chang et al, 2017; Kotlarsky et al. 2020; Lee et al. 2019). Emerging technologies emphasize the need of expanding this theoretical base and accommodating new paradigms of capturing and analysing data in IS sourcing research.

Taking into account the above observations, the IS sourcing literature thus begs for the re-examination of client-supplier-advisory relationships by challenging core concepts of sourcing decision, contractual structure and relationship management as offering new theoretical landscapes that accommodate the sourcing phenomenon in a digital age. This special issue seeks to facilitate an empirical and theoretical re-examination of “IS sourcing” in the light of the current wave of emerging technologies. Areas of interest to the special issue include but not limited to:

 Governance and control structures between client-supplier-advisory in emerging technology settings;  Sourcing decision making in emerging technology settings;  Ecosystem and platforms in emerging technology sourcing settings;  Contract management in emerging technology sourcing settings;  Full data lifecycle in emerging technologies and its implications for sourcing management;  Skills and capability development and retention in emerging technology sourcing settings;  Implications for innovations within the client-supplier-advisory eco- system;  Ethical and societal implications deriving from such sourcing settings;  Impact of emerging technologies on client’s, supplier’s and advisory’s strategies, business models and capabilities (e.g., has offshoring slowed down/back sourcing accelerated? And what was the impact on captive centers’ services).  Implications of “crowdsourcing”, big data, analytics as well as machine/deep learning and artificial intelligence for the contemporary IS outsourcing.

We invite research papers that investigate issues relating to emerging technologies and IS sourcing. In particular, we take interest in issues concerning robotic process automation, big data, machine/deep learning and artificial intelligence and blockchain. Other technologies are less of interest for this special issue (contact the special issue editors if in doubt).

There will be a developmental workshop connected to this special issue. Participation in the workshop not mandatory for submission to the special issue, but strongly encouraged.

Guidelines for Extended Abstract Submission:

Please construct your submission as follows: 1. Introduction and clear motivation 2. Brief literature review and theoretical foundations 3. Empirical base of the study 4. Expected contribution

Submission Timetable

- Submission of extended abstract for workshop: 30th September 2020 - Feedback on abstract to authors: 30th October 2020 - JIT Special Issue Workshop – Pre- or post-ICIS Advance IS Sourcing SIG Workshop (to take place online to accommodate authors who are not able to travel to ICIS) - First round submission: 26th February 2021 - First round decision to authors: 28th May 2021 - Second round submission: 13th August 2021 - Second round decision to authors: 19th November 2021 - Third and final round submissions: 28th January 2022 - Final decision to authors: 11th March 2022

JIT submission guidelines: https://journals.sagepub.com/author-instructions/JIN

References

Brynjolfsson, E. and McAfee, A. 2016. The second machine age: Work, progress, and prosperity in a time of brilliant technologies. Norton, New York (2016) Chang, Y. B., Gurbaxani, V., and Ravindran, K. 2017. Information technology outsourcing: asset transfer and the role of contract, MIS Quarterly 41(3), 959-973. Coombs, C., Hislop, D. Taneva, S.K. and Barnard, S. 2020. The strategic impacts of Intelligent Automation for knowledge and service work: An interdisciplinary review. The Journal of Strategic Information Systems. Dibbern, J., Goles, T., Hirschheim, R., Jayatilaka, B., 2004. Information systems outsourcing: A survey and analysis of the literature. Database for Advances in Information Systems 35 (4), 6-102. Du, W.(D)., Pan, S.L., Leidner D.E. and Ying, W. 2019. Affordances, experimentation and actualization of FinTech: A blockchain implementation study. The Journal of Strategic Information Systems 28(1), 50-65. Karimi-Alaghehband, F., Rivard, S., Wu, S., Goyette, S., 2011. An assessment of the use of transaction-cost theory in information technology outsourcing. The Journal of Strategic Information Systems 20 (2), 125–138. Kotlarsky, J., Oshri, I., Dibbern, J., Mani, D., 2020. MISQ research curation on IS sourcing (https://www.misqresearchcurations.org). Lacity, M.C., Willcocks, L.P., 2016. A new approach to automating services. MIT Sloan Management Review 58 41–49 Lee, J-N., Park, Y., Straub, D.W., Koo, Y., 2019. Holistic Archetypes of IT Outsourcing Strategy: A contingency fit and configurational approach. MIS Quarterly 43(4), 1201-1225. Wiener, M., Saunders, C and Marabelli, M. 2020. Big-data business models: A critical literature review and multi-perspective research framework. Journal of Information Technology 35(1), 66-91

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