UCUMBERLANDS A Learning Model of Information Technology Outsourcing Article Analysis Write summary of the theory, research design, analysis, and conclusion

UCUMBERLANDS A Learning Model of Information Technology Outsourcing Article Analysis Write summary of the theory, research design, analysis, and conclusions for the article attached in 2 pages each for an article.Attaching 2 articles and write above described section. A Learning Model of Information
Technology Outsourcing: Normative
Implications
Hoon S. Cha, David E. Pingry, and Matt E. Thatcher
Hoon S. Cha is an Assistant Professor of Information and Decision Sciences at the
Franklin P. Perdue School of Business, Salisbury University. He holds an M.S. and
Ph.D. in Management Information Systems from the University of Arizona and a B.S.
in Material Sciences and Engineering from Seoul National University. He worked for
Samsung for three years as an IT consultant. His research examines the impact of IT
offshoring decisions on firm knowledge and costs and the allocation of IT investment
among business functions and its effects on business value.
David E. Pingry is McClelland Professor of Management Information Systems and
Economics at the Eller College of Management, University of Arizona, where he
has been since 1974. He holds a Ph.D. in Economics from Purdue University and an
A.B. in Economics from the University of Illinois. Professor Pingry was also on the
faculty at Virginia Tech, held visiting faculty positions at Purdue University and Texas
A&M, and held the Treibick Visiting Endowed Chair in the Connecticut Information
Technology Institute at the University of Connecticut. His current interests are decision support systems, patent policy, and IT productivity.
Matt E. Thatcher is an Associate Professor of Computer Information Systems at the
College of Business, University of Louisville. He holds a B.S. in Economics and an
M.A. and Ph.D. in Information Systems from the Wharton School of the University
of Pennsylvania. His research examines the strategic and economic effects of IT with
a focus on four themes: IT value, software patent policy design, IT outsourcing, and
the social costs of information privacy. His work has appeared in Information Systems
Research, Journal of Management Information Systems, MIS Quarterly, Communications of the ACM, Decision Support Systems, Journal of Strategic Information Systems,
Journal of Financial Services Research, and Journal of Information Technology Theory
and Application.
Abstract: We use an economic learning model to examine how knowledge parameters
characterizing a sourcing relationship between a vendor and a client interact with
production costs and coordination costs to affect the business value of alternative
outsourcing strategies. This information is then used to determine a firm’s optimal rate
of information technology (IT) outsourcing. We find that the optimal outsourcing rate
is dependent on the ability of the outsourcing client to acquire production knowledge
from its outsourcing vendor and to retain its internal coordination knowledge despite
losses of fundamental production skills due to outsourcing. Specifically, when the
client is unable to acquire sufficient production knowledge from the external vendor,
the client’s optimal outsourcing decision is to engage in either one of two extreme
Journal of Management Information Systems / Fall 2009, Vol. 26, No. 2, pp. 147–176.
© 2009 M.E. Sharpe, Inc.
0742–1222 / 2009 $9.50 + 0.00.
DOI 10.2753/MIS0742-1222260207
148
Cha, Pingry, and Thatcher
strategies—total insourcing or total outsourcing—depending on the rate at which
the client’s coordination knowledge depreciates. On the other hand, when the client
is able to acquire a substantial amount of production knowledge from the external
vendor, the firm’s optimal decision is to outsource only a portion of its IT services,
where the proportion depends on the rate at which the client’s coordination knowledge
depreciates.
Key words and phrases: coordination, economic analysis, IT outsourcing, knowledge, modeling, organizational learning, outsourcing, production costs, vendor–client
relationship.
To meet growing information technology (IT) needs, an increasing number of firms
have decided to outsource some or all of their IT functions and services—such as
software development, production, and maintenance—to highly skilled external
vendors with scale economies. In today’s competitive business environment, IT
managers must identify the factors and circumstances that determine the optimal
rate of IT outsourcing for their firms. This paper focuses on the critical role that the
accumulation and loss of knowledge plays in determining a firm’s optimal rate of IT
outsourcing. Specifically, we extend the mathematical learning model of Cha et al. [9]
to develop normative statements about how much of its IT function a firm should
outsource. Using these normative findings, we are able to explain findings from two
mini-cases and an empirical study that focus on IT outsourcing relationships in the
financial services industry.
The academic literature has produced many studies that have examined various
factors that drive a firm’s IT outsourcing decision. These factors include lower production costs of outsourcing vendors due to their superior production economies and
technical expertise [3, 32, 40]; a firm’s need to focus on its core competencies [21,
24, 31]; societal and industry-level characteristics [2, 23]; firm-level characteristics
such as financial characteristics [3, 32, 40, 42], firm demographics [3, 39, 41], and
strategic focus [22, 39]; and IT-level characteristics [2, 6, 34, 42]. For an extensive
survey and analysis of the many theories used to explain various outsourcing decisions
and arrangements, see Dibbern et al. [16].
More related to this paper is work that has examined a firm’s outsourcing decisions
based on transaction cost theory [33]. According to transaction cost theory, a firm
incurs two types of costs to provide any product or service—production costs and
coordination costs. Production costs are the costs incurred to make the product or
provide the service and includes the cost of labor, material, and capital. Coordination
costs are the costs incurred to monitor, control, and manage the work. For example,
in order to develop and implement a software application, a firm must perform a
sequence of related knowledge-based processes. This requires that a firm engage in
lower-level production processes such as research, analysis, design, coding, testing,
and maintenance of the specific software application. It also requires that a firm engage
A Learning Model of Information Technology Outsourcing
149
in higher-level coordination or managerial processes such as developing IT strategy
and development priorities and integrating new applications with existing internal
resources to solve business problems [43]. Production and coordination processes
generate specific costs. A firm determines its optimal degree of outsourcing based
on the trade-off between the lower production costs and higher coordination costs
associated with outsourcing [37, 38].
In addition, production processes and coordination processes each require specific
knowledge. Both of these stocks of knowledge can be enhanced through learning
by doing (usually assumed to be a function of the level of production), and both are
subject to knowledge depreciation from technology obsolescence, poor general and
knowledge management strategies, and employee turnover. Further, the ability of
project managers to effectively manage the higher-level coordination processes and
integrative activities depends critically on the firm’s experience with performing the
lower-level production processes.
Given that learning by doing is a function of the level of production, a firm that
outsources its development activities may lose much of its experiential production
knowledge over time. This erosion of production knowledge will in turn increase the
firm’s internal marginal production costs (related to IT activities that remain in-house)
and diminish the ability of managers to effectively coordinate and integrate the outsourced IT activities with the firm’s existing internal activities [43]. It is particularly
difficult to coordinate these outsourced activities given how pervasive IT is throughout
the firm and how interrelated IT is with most firm processes and activities [44]. Firms
must accumulate and retain experiential production knowledge about outsourced IT
functions in order to effectively coordinate and integrate them with the firm’s existing processes. Failure to do so may reduce, or even completely eliminate, the initial
production cost savings often associated with IT outsourcing [1, 9].
On the other hand, an outsourcing client may be able to capture a portion of its
vendor’s production knowledge for its own internal use. Often, vendors are in a
position, due to their higher levels of production, to accumulate large repositories of
learning-by-doing production knowledge. A client may be able to acquire a portion of
the vendor’s relevant and useful production knowledge through several mechanisms.
For example,
• An outsourcing client may require, by contract, that the vendor transfer a portion of its production knowledge to the client through a mentoring program that
makes vendor employees accountable for transferring to client employees the IT
skills and knowledge necessary to maintain IT competencies and achieve their
internal production goals for those IT projects that remain in-house.
• An outsourcing client may invest in collaborative application development systems and group decision support systems that improve the communication and
collaboration between client and vendor, thus improving the client’s ability to
acquire production knowledge from the vendor.
• An outsourcing client may require, by contract, that the vendor embed a small
set of the client’s employees on the outsourced projects. These embedded employees would not only provide domain expertise to the vendor but also, and
150
Cha, Pingry, and Thatcher
perhaps more important, allow the client to acquire, from the vendor, production
knowledge that may be used to improve the client’s production processes that
remain in‑house.
Thus, while higher outsourcing rates reduce the client’s learning-by-doing experience [1, 12, 14, 15, 18, 29, 30, 43], they may also increase the opportunity for the
client to acquire new and useful production knowledge from its highly skilled vendors
with scale economies [13]. As a firm increases its outsourcing rate, there is a trade-off
between the benefits associated with gaining production knowledge through knowledge
transfers from the vendor and the costs associated with losing internal learning-bydoing experiences. The resulting impact of outsourcing on the client’s own repository
of production knowledge, and therefore total production cost, is ambiguous. However,
higher outsourcing rates, and the associated loss of experiential knowledge, tend to
hinder the client’s ability to coordinate and integrate the IT activities with its existing
business processes. This represents a reduction in the client’s repository of coordination
knowledge and, therefore, an increase in its coordination costs. Given these various
knowledge flows and their links to production and coordination costs, the impact of
outsourcing on total cost is ambiguous.
There are many empirical studies that illustrate the significant effects of a firm’s
knowledge of, and experience with, IT on firm costs [11, 17, 26, 27, 36]. Some of the
knowledge flows in outsourcing have been discussed in prior work [1, 12, 13, 14, 15,
18, 29, 30, 43]. However, the analysis presented in this paper builds specifically on a
learning-based outsourcing model developed by Cha et al. [9]. Cha et al. incorporated
transaction cost theory into an economic learning model and then used this model to
determine the business value of a single, selective outsourcing strategy where the client outsources half of its IT functions. They then examined the dynamic relationship
between firm knowledge and costs over the life of the IT project under this strategy
and determined the conditions (e.g., project length and knowledge assumptions) under
which a firm would prefer to outsource and backsource its IT functions.
In contrast, we extend the learning-based outsourcing model and expand the analysis
to determine the business value of a full range of outsourcing strategies in different
knowledge environments. This allows us to make normative statements about how
much of its IT function a firm should outsource in different circumstances. In order
to gain this new perspective, we relax two of the critical assumptions of Cha et al.’s
model. First, we treat the outsourcing rate as an endogenous variable as opposed to
an exogenous variable. This relaxation allows us to examine a firm’s outsourcing rate
as a strategic decision and to examine the knowledge environments in which different
outsourcing strategies, including total insourcing, total outsourcing, and all selective
outsourcing strategies in between, may minimize a firm’s total costs. Second, we
model the knowledge transfer rate (i.e., that rate at which the client acquires production
knowledge from the vendor) as an increasing function of the outsourcing rate. That
is, we acknowledge that the rate at which a client acquires knowledge through vendor
transfers may depend on the extent of the outsourcing relationship. These extensions
allow us to derive new managerial insights into outsourcing decisions made by firms
in a range of industries, including banking and insurance.
A Learning Model of Information Technology Outsourcing
151
Figure 1. Results Summary
The analysis of the model is accomplished by creating four scenarios, each representing a different combination of two critical knowledge parameters. The production
knowledge transfer rate represents the ability of the client to capture production knowledge from the vendor. The coordination knowledge depreciation rate represents the
ability of the client to retain coordination knowledge as it outsources its IT activities.
This parameter captures the impact of the loss of client learning-by-doing knowledge
on client coordination knowledge.
The critical findings are summarized in Figure 1. We find that when the rate at which
the vendor transfers production knowledge to the client is relatively low, the client’s
optimal outsourcing decision is to engage in either one of two extreme strategies—total
insourcing or total outsourcing. The optimal choice depends on the rate at which the
client’s coordination knowledge depreciates. Specifically, if the depreciation rate of the
client’s coordination knowledge is low, then the client will minimize costs through a
total outsourcing strategy; otherwise, if the depreciation rate of the client’s coordination knowledge is relatively high, then the client will minimize costs through a total
insourcing strategy (i.e., keeping all of its IT activities in-house).
On the other hand, we find that when the rate at which the vendor transfers production
knowledge to the client is relatively high, the firm’s optimal decision is to implement
a selective outsourcing strategy in which the firm outsources only a portion of its IT
services. In this case, the optimal rate of IT outsourcing also depends on the rate at
which the client’s coordination knowledge depreciates; that is, the lower the depreciation rate, the higher is the optimal rate of IT outsourcing. Later in the paper, these
results are interpreted in the contexts of two mini-cases and a recent empirical study
that focus on IT outsourcing relationships. In these contexts, we discuss how firms
may be able to invest in various knowledge management strategies and technologies
and other organizational capabilities to influence the knowledge environment and
create the conditions for successful outsourcing.
152
Cha, Pingry, and Thatcher
The Learning-Based Outsourcing Model
We assume that the client firm produces a total quantity q of IT services and that
the firm may decide to outsource any proportion (0 ≤ α ≤ 1)1 of its IT services to an
outside vendor, which has lower production costs than the client firm. The outsourcing rate is determined at the beginning of the contract and is fixed over the life of the
contract. The vendor accepts this contract without negotiation (similar to a leader–
follower relationship). The contract is a time-and-materials contract where the vendor’s
production costs are passed directly to the client firm.
We assume that (1) firm costs vary inversely with the firm’s knowledge level and
(2) the marginal change in a firm’s knowledge level is a function of its quantity of
output, rate of knowledge transfer, and rate of knowledge depreciation. The derivations
of the specific production and coordination knowledge/cost relationships are presented
in Appendix A. The critical model parameters and relationships are summarized below
and in Table 1. For the cases discussed later, the numeric values of the exogenous
parameters are set to reflect a situation where the vendor has lower unit production
costs and a larger scale than the client firm for the outsourced activity.
In our analysis, we want to determine the total cost to the client firm of outsourcing
strategies, ranging from total insourcing to total outsourcing, in different knowledge
environments, and identify the optimal degree of IT outsourcing in each environment.
The total cost incurred by the client firm is the sum of all production costs and coordination costs. The vendor’s production costs are a function of its repository of production
knowledge. The vendor accumulates experiential production knowledge by producing
a quantity of aq + D IT services for all of its clients. The more IT services the vendor
produces for its clients, the larger is its repository of production knowledge and the
lower are its production costs. However, the vendor also loses some of its repository
of production knowledge over time through depreciation at a rate of dPR.
The client maintains two repositories of knowledge: a repository of production
knowledge that supports its production of the IT services that remain in-house and a
repository of coordination knowledge that supports the integration of the outsourced
activities with the firm’s internal resources, which allows the firm to solve business
problems and implement firm strategies. Like the vendor, the client loses some of its
repository of production knowledge over time through depreciation at a rate of dPR.
However, the client accumulates new experiential production knowledge by producing
the quantity of (1 – a)q IT services that remains in-house. In addition, the client may
use different mechanisms to accumulate new and useful production knowledge at a
rate of t from the vendor, where the amount of knowledge acquired from the vendor
is t(aq + D). We assume that the proportion of production knowledge transferred
from the vendor to the client firm increases with the outsourcing rate α—or the extent
_
_
_
of the outsourcing relationship—such that t = at , (0 ≤ t ≤ 1), where t is the upper
boundary of the knowledge transfer rate when the firm outsources all of its services.
So, as the client increases its outsourcing rate, there is a trade-off between benefits
associated with acquiring production knowledge from the vendor and costs associated
with losing experiential production knowledge.
This is the rate at which the production knowledge of both firms depreciates over time. Some
knowledge is lost over time because of technology obsolescence, imperfect knowledge management
practices, employee turnover, and other factors.
This is the rate at which the client firm accumulates production knowledge through knowledge
transfers from the external vendor. We assume that the proportion of the vendor’s production
_
_
knowledge acquired by the client increases with the outsourcing rate such that t = at , (0 ≤ t ≤ 1).
This is the rate at which the coordination knowledge of the client firm depreciates over time. If a
firm outsources its p…
Purchase answer to see full
attachment