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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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