2014 47th Hawaii International Conference on System Science
IT Investments and Firm Stock Market Value: The Mediating Role of Stock
Analysts
Xueming Luo
Temple University
[email protected]
Bin Gu
Arizona State University
[email protected]
investments depends on how firms leverage the
technology and cannot be assessed without a full
understanding of a firm’s business strategies and
organizational resources. Substantial research has
been conducted to look inside the firm to identify the
strategies, processes and resources that help generate
value from IT investments.
What is often neglected in this internal view of IT
investment is that IT and its role within a firm is not
only difficult to evaluate for the management but also
difficult to evaluate for external investors who
ultimately determine firms market value. Echoing
this, [12] lamented: “many firms do not report the IT
intangible assets on their balance sheets, forcing
investors to rely on other sources of information to
value these assets.” This lack of observability of IT
and the related strategies, processes and resources to
external investors creates significant information
asymmetry in the financial market. Without bridging
this information asymmetry, it is challenging for the
financial market to accurately assess the value of IT
investments.
Thus, there is a demand for external information
intermediaries to help the market better understand
firms’ IT investments and their value. A key
information intermediary that affords such
responsibility is stock analysts [46]. Stock analysts
are employed by financial institutions such as stock
brokerages, banks and financial consulting firms to
collect and compile information from various
sources, examine firm fundamentals, evaluate firm
performance, and provide informed recommendations
and forecasts of firm future earnings to institutional
and/or retail investors [37]. In this way, they aid
investors’ interpretation of firms’ tangible and
intangible investment [40]. The stock analysts’ role
in interpreting firms’ behavior suggest that they may
channel and certify the effects of firms’ IT
investment on their market valuation.
The goal of our study, therefore, is to investigate
following questions: (1) Do analysts mediate the
effects of firms’ IT systems on firm market value,
i.e., help the market discover the business value of IT
investments by firms? (2) What types of IT systems
rely more on the mediating role of stock analysts?
Abstract
This study provides a new perspective to the longstanding debate on the business value of IT. Prior
research on IT value takes an internal perspective –
focusing on business processes and complementary
resources that help create value form IT investments.
In this study, we take an external perspective –
focusing on the value discovery role of stock analysts.
Stock analysts collect information about firms’ IT
investments and provide informed recommendations
to investors in the financial market. Research in
finance has long shown that stock analysts can
reduce information asymmetry between the firm and
investors. However, despite that IT investments are
known for their complexity and inherent risks, little is
known about the role of stock analysts in helping the
financial market understand firms’ investments in IT.
We address this question empirically using IT assets
and firm performance data of Fortune 1000 firms
between 1996 and 2007. Our empirical evidence
suggests that stock analysts play an intricate
mediating role in the stock market evaluation of IT
investments. Analyst recommendations have a
stronger mediating role in the effects of enterprise IT
systems (ERP and CRM) on firm market value, but a
weaker and insignificant mediating role in the effects
of function IT systems (DSS, HR and AIS). In
addition, we find that the mediating role of financial
analysts for IT investments is more salient when the
firm’s market environments are more uncertain and
unpredictable. These findings suggest that financial
analysts play a critical role in the market valuation of
firms’ IT investments.
1. Introduction
IT investment is an important element in firms’
value creation process and has grown to be the largest
category of capital expenditures in businesses.
Research has extensively investigated the effect of IT
investments on firms’ performance [41, 49]. A key
insight of prior research is the “general purpose”
nature of IT [4, 7, 11]. As such, the value of IT
978-1-4799-2504-9/14 $31.00 © 2014 IEEE
DOI 10.1109/HICSS.2014.505
Cheng Zhang
Fudan University
[email protected]
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And (3) is this mediating role more or less salient for
firms in uncertain market environments.
We assess this question empirically using IT
assets and firm performance data of Fortune 100
firms between 1996 and 2007. The IT and firm
performance data are obtained from Harte-Hanks and
Compustat respectively. Our analysis shows that
stock analysts’ recommendation has a significant
mediating effect on the financial market’s evaluation
of IT investments. The mediating effect varies by IT
investment type. Analyst recommendations have a
stronger mediating effect for firms investing in
enterprise IT systems (ERP and CRM) than those
investing in functional IT systems (DSS, HR and
AIS). Our analysis suggests that stock analysts
provide a critical function in helping financial
markets discover the business value of IT
investments, especially investments in sophisticated
enterprise IT systems and for firms operating in more
uncertain and unpredictable market environments.
The rest of the paper is organized as follows.
Section 2 provides a review of literatures on IT
investment and on the role of stock analysts as well
as our contribution to the literatures. Section 3
develops hypotheses for the analysis. Section 4
presents the research context, data and empirical
approach. Section 5 discusses the results. We
conclude in Section 6.
enterprise resource planning [33], customer
relationship
management
[31],
knowledge
management systems [54], e-commerce [22], supply
chain management systems [21], and other IT
infrastructure applications [17] studies reveal
significant variations in the market value of these IT
applications. We contribute to this stream of
literatures by offering a new explanation of the
phenomenon. We propose that the mediating effect of
stock analysts varies significantly with the
complexity and intangibility of the IT application.
Our study is also related to prior IS studies that
use market-based measure in assessing the business
value of IT investments. The underlying assumption
of market-based measures is that the financial market
fully reflects the value of IT investments. Our study
suggests that this is not necessarily the same. Stock
analysts play an important role in helping the market
assess the value of IT investments. If a firm is not or
barely reflected by stock analysts, market-based
measures may underestimate the business value of IT
for these firms. Our study contributes to the IT
literature by highlighting the role of stock analysts in
discovering the value of IT investment. Our study
also adds to emerging studies that examine stock
analysts’ information-giving behaviors on market
information environment and market valuation [60
and their recommendation as risk measures [22, 23].
2. Literature Review
3. Research Framework and Hypothesis
Development
The study is related to two streams of literatures.
The first stream is on the business value of IT. This
stream of literature has extensively analyzed the
internal processes that relate a firm’s IT investments
to its market performance [7]. For example, pointing
out the missing links between IT investment and firm
performance, Zhu and Kraemer [65] explain IT usage
breadth and depth are critical internal mechanisms
that explain why IT investments can lead to firm
performance. Similarly, IT-related business processes
[49] and dynamic capabilities [38] are documented as
the important intermediary outcomes between IT
investments and organizational performance, all of
which can potentially create firm financial value in
the stock market. Extending this internal processoriented view of IT investment, our study takes an
external process-oriented view of IT valuation. We
propose that external analysts, particularly
recommendations from stock analysts, facilitate
investors to interpret and price the potential value of
IT investments ultimately in the stock market.
Prior literatures of business value of IT have also
considered specific IT applications, including
3.1. Stock Analysts
As industry experts, stock analysts work as
information intermediaries between firms and
investors. Analysts are also more skilled and efficient
at analyzing the value relevance of public
information and can gather a wider variety of
information than individual ordinary investors. They
provide additional value contained in stock
recommendations to investors [46]. Therefore, they
play as an important role to link the firms’ actions to
market valuation of firms [46].
There are ample anecdotal evidences indicating
how analysts influence IT value in practice. For
example, when Lindsay invested an enterprise
resource planning system in the fourth quarter of
2011 which resulted in cost increased, analysts
foresaw the benefit from efficiency improvement in
fast-growing
irrigation
markets
and
thus
recommended investors to buy Lindsay’s stock
strongly. Similarly, although Amedisys was facing
difficulty, analysts reported that the firm’s customer
relationship management (CRM) tool could help the
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H1: Holding everything constant, analyst stock
recommendations mediate the effects of IT investment
on firm market value.
firm’s internal growth by increasing its managed care
services and forming value-added relationships with
customers, and thus recommended investors to keep
neutral to the firm’s stock. On the contrary, when
Dell invested and developed new data management
solution to improve the decision-making efficiency of
their mid-sized organization clients in July 2012,
analysts were concerned several macroeconomic
factors, finance market uncertainty and certain sales
execution issues the firm was facing might delay the
revenue recognition process, and finally suggested
investors to sell the firm’s stock.
3.3. Moderating Effect of Enterprise IT
Depending on the scope of the complementary
organizational resource required by the IT
investment, two categories of IT systems are
important: functional IT and enterprise IT [13, 48].
The former refers to investments that comprise
specific function-level IT-enabled resources such as
accounting and HR, while the latter refers to
investments that comprise enterprise-wide IT-enabled
resources such as enterprise resource planning,
customer relationship management and supply chain
management that must be built and cultivated over
time [43]. Functional IT facilitates specific discrete
business operations like accounting and human
resource management without affecting other
business operations, while enterprise IT often
requires integration of substantial complementary
organizational resources across multiple business
operations and units such as synthesizing long-term
relationship building with customers on an crossspanning infrastructure by customer relationship
management (CRM) systems [31].
We expect that analyst recommendations have a
stronger mediating effect on firm market value with
enterprise IT investments than that with functional IT
investment. First, firm’s benefit from of enterprise
IT, particularly its strategic and long-term value, is
harder to evaluate than that from functional IT. Given
the intangible and future-growth nature, enterprise IT
provides growth options for future initiatives, but
usually with high short-term cost a learning effort
[49]. For example, consider a firm that is planning to
implement a CRM application in order to better
understand consumer preferences. Although such an
application can favorably affect a firm’s strategic
advantage in the market, such advantage is hard to
value by normal individual investors when the firm
implements the system until the firm achieves
success in the future [32]. Thus it requires
professional experience and capability to estimate the
current value of enterprise IT accurately. In this way,
stock analyst contributes to the value discovery of
enterprise IT investment and reduces information
asymmetry between firms and investors significantly.
Second, enterprise IT typically enables a firm to
expand its strategic potential by changing the way
organizational complementary resources operate.
Taking the CRM as example again, it requires much
more than IT itself by focusing on in-depth and
usually cross-spanning integration with various
complementary organizational resources [25], and
3.2. Mediating Effect of Analysts
IT investments are signals of future performance
of the firm. However, such signals are either not
disclosed or sparsely distributed to the public due to
the lack of information disclosure [12]. Thus, there is
incomplete information of IT investments, which
creates information asymmetry and market
inefficiency. So investors may not always timely
analyze IT investments and even fail to accurately
price IT investments in firm stock prices.
Given the information intermediary functions of
stock analysts, we expect analyst recommendations
partially mediate the effects of IT investment on firm
market value for two reasons. First, analysts collect
and reveal firms’ public and private information to
the market [36]. Stock analysts’ function is to
aggregate information from multiple sources and
presents the information in an integrated manner to
investors, thus likely reducing the information
asymmetry between firms’ IT system performance
prospects and investors in the financial markets. This
suggests a chained effect, i.e., the firm information is
channeled by analysts’ recommendations to influence
the market valuation of firms by investors [46].
Second, due to intangible nature of IT investment
and the need for complementary process changes and
resource, a large amount of the information needed to
evaluate a firm’s IT investment cannot be easily
accessed by investors. Analysts can obtain firmspecific information through their connections within
the firm and the industry to help investors gauge
future cash flows and firm value [57]. Thus, the
forecast and recommendation by stock analyst is
more likely to reflect the true value of the firm and be
accepted by investors [36]. Thus, stock analyst’
recommendation channel the effects of IT investment
on firm value by providing investors with additional
information and knowledge on firms’ IT investment.
The recommendations aid investors’ interpretation of
firms’ IT investment, thus allowing the market to
overcome the challenge of valuing the intangible IT
value. Thus, we posit that:
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consequently, makes information more ambiguous
and unclear to investors. As stock analysts have
stronger information seeking and processing ability
than normal individual investors, they can provide
more complete information of firms’ action with
professional analysis to help investors understand,
which also results in information asymmetry
reduction. from are more important to the value
discovery process to understand the nature of
complementary organizational resources and quantify
the value of enterprise application [25, 51].
Functional IT is opposite case of enterprise IT. It
is expected to solve firms’ some short-term
challenges and are directly necessary for firms’
certain discrete tasks. With a clear short-term
expectation, its present value is easy to define and
estimate. With a clear scope, firms’ other resources
outside the scope are not influenced by IT.
Consequently, necessary information to value
functional IT is straightforward to collect and
process. In such situations, the expertise of stock
analysts is less important to the value discovery
process of IT. Therefore, we posit that:
H2: Analyst recommendations have a stronger
mediating effect on firm market value with enterprise
IT investments (ERP and CRM) than that with
functional IT investment (DSS, HR and AIS).
consequently help firms’ IT value realization.
Overall, we expect higher uncertain market
environments increase needs of the information
expert of analysts to discover value from IT signal
prospect. So we posit that:
H3: Analyst recommendations have a stronger
mediating effect on firm market value in a more
uncertain market environment.
4. Data and Measures
In testing the hypotheses, we collect data on IT
investments, analyst stock recommendations, firm
stock market value, and a set of control variables.
There are multiple sources involved, including the
Harte-Hanks Surveys, Institutional Brokers’ Estimate
System (I/B/E/S), the Center for Research of
Securities Prices (CRSP), and COMPUSTAT. As a
result of merging these data sources, we had 3,236
pooled firm-year observations between 1996 and
2007.
IT investment data. We obtained IT investment
data from Harte-Hanks.
Harte-Hanks conducts
annual surveys of IT systems and IT assets of Fortune
1000 firms.
The survey is conducted at the
establishment level with over 500,000 establishments
contacted. It covers ten key IT areas, including
personal computing, systems and servers,
networking, software, storage, managed services and
others. The survey is intended for clients in the IT
industry, so it contains detailed information about the
vendor and type of every IT system used by the firm.
Various versions of this database have been used in
prior research in the IS literature [e.g., 28, 61, 65].
We use the Harte-Hanks data to obtain two
measures of IT investments for each firm. First, we
estimate the total amount of IT investments for each
firm based on the total number of PC, servers, and IT
employees reported through the survey. We follow
the approach used by - that estimates a firm’s totally
IT investments as the sum of PC and server capital
plus three times the IT labor costs. We obtain yearly
PC prices from Gartner Dataquest Global PC Annual
Forecast, and yearly server prices from IDC
Worldwide Server Quarterly Tracker. We adjust the
nominal prices to real prices using the Bureau of
Economic Analysis (BEA) price index for Computers
and Peripheral Equipment [7]. Industry-average labor
compensation is obtained from occupational
compensation data reported by the Bureau of Labor
Statistics (BLS), deflated by the Index of Total
Compensation Cost. Second, we categorize IT
systems into five types: Enterprise Resource Planning
(ERP), Customer Relationship Management (CRM),
3.4. Moderating Effect of Uncertain Market
Environments
We also expect analyst recommendations have a
stronger mediating effect on firm market value in
more uncertain market environments. First, IT
investment has uncertain payoffs [1], particularly
when firms are facing uncertain market demand for
the firm's product and services [3]. As market
demand uncertainty for product or service [20]
cannot be managed or reduced by a single firm – [8],
greater uncertainties in markets increase the
investors’ difficulty of understanding firms’ return
and risk [2]. To overcome the incomplete knowledge
or inability of processing information [8, 42, 50],
investors
are
more
relied
on
analyst
recommendations for credible signal of firm IT
investment’ true profitability and market value when
the firm is in more rather than less uncertain market
environments [16].
Second, IT value varies with the demand for the
future business applications [20]. As higher uncertain
market environments increase the demand
uncertainty for future business, it brings more
uncertainty to IT’s future value consequently. In the
situation, stock analyst’s expertise and more
complete information facilitate investors to
understand firms’ IT value more accurately and
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and is the model residual. We then calculate
abnormal returns ( ) as the difference between
the observed returns and the expected returns, as
follows:
= ( − ) − + − +
+ + (2)
Control variables
To rule out many alternative explanations of our
results and more robustly identify the hypothesized
effects, we have a comprehensive set of firm-,
analyst- and industry-level covariates. We closely
follow the widely used models of financial analyst
metrics [37, 42] and firm stock value in finance and
accounting [27, 43] to select a large set of relevant
covariates. This allows us to calibrate the extent to
which IT investments contribute new information in
explaining analyst stock recommendations and the
mediating role of analyst stock recommendations in
channeling the effects of IT investments on firm
stock market value after controlling for many factors.
Specifically, firm profitability (ROA) is measured
as the ratio of a firm’s operating income (from
Compustat) to its book value of total assets. ROA
variability is measured as the standard deviation of
the reported prior five years of ROA. We control for
ROA and its variability because prior finance studies
have found that firm profitability and ROA
variability contain firm fundamentals information and
likely affect analyst stock recommendations and firm
value [43, 58].
R&D intensity is measured as research and
development expenses divided by sales. Prior studies
found
that
R&D
affects
analyst
stock
recommendations and firm market value [6, 58].
New product announcements are the number of
new products introduced by the firm and collected
from the Lexis/Nexis news search. New product
announcements reflect the commercialization aspect
of IT capabilities of the firm. Prior studies have also
used Lexis/Nexis news search to measure new
product announcements [56].
Firm size is the measured as the total asset of the
firm. By and large, the bigger the firm size, the more
resources the firm has to support IT investments [51].
Advertising intensity is measured as the firm’s
advertising expenses divided by sales revenue. Prior
studies [44] found that advertising affects firm stock
prices.
Firm financial leverage is the ratio of long-term
book debt to total assets [58]. Because financial
leverage reflects firm capital structure and firm stock
prices, we control for its effects while testing the
impact of IT investment on analyst recommendations.
Firm dividend is the ratio of cash dividends to
firm market capitalization. Because the firm’s
Decision Support Systems (DSS), Human Resource
Systems (HR) and Accounting Information Systems
(AIS). For each type of IT systems, we count the
number of business establishments of each firm that
report using such systems as an indicator of the
prevalence of the particular type of IT systems in the
firm. Table 1 reports the summary statistics of IT
investments.
Mean
Median
Std dev
Min
Max
IT Inv.
Total
(log)
3.87
3.71
1.38
0.69
8.08
IT Inv.
AIS
(log)
1.84
1.79
1.27
0
6.12
IT Inv.
DSS
(log)
0.9721
0
1.59
0
6.18
IT Inv.
HR
(log)
1.05
1.09
0.98
0
5.14
IT Inv.
CRM
(log)
0.67
0.69
0.82
0
4.25
Table 1: Summary Statistics of IT Investments
Analyst stock recommendations. Data for
analysts’ stock recommendations are from I/B/E/S.
For publicly-traded companies, I/B/E/S provides
comprehensive
data
on
stock
analysts’
recommendations, earnings forecasts, and other
financial indicator of the firm [59]. Though new to
the IS discipline, I/B/E/S has been widely used in
finance, marketing, and accounting fields [9, 27, 30,
46]. I/B/E/S has data for over 45,000 companies
from 70 stock markets worldwide. Because multiple
stock analysts follow each publicly traded company,
and each analyst provides multiple investment
recommendations for each company, we originally
collected a total of 339,068 observations of analyst
stock recommendations. I/B/E/S measures analyst
recommendations as the median consensus of buyhold-sell recommendations provided by analysts to
investors [35]. As the raw data is in a reversed Likert
scale (with 1 = strong buy, 2 = buy, 3 = hold, 4 =
under-perform, and 5 = sell), we transformed this
reverse coding for ease of exposition (so 5 = strong
buy).
Firm stock market value. We measure firm
stock market value with the abnormal returns of the
firm in the stock market, over and beyond what is
expected from the broad financial markets after
adjusting market wide risk factors [10]. We obtained
stock price data from CRSP to derive firm abnormal
returns. To measure expected return from the broad
financial markets, we use the Fama-French-Carhart
model at the firm level as follows:
− = + − + +
+ + (1)
where are returns for firm i on time t, are
average market returns, is the risk-free rate, are size effects, are value effects, are
Carhart’s momentum effects, is the intercept,
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dividend payment is valued by stock analysts and
investors,
it
would
influence
analyst
recommendations and firm value [40].
Firm liquidity is the current ratio of a firm. We
control for this variable because compared to fixed
assets, liquid assets are related to less volatile returns
and thus preferred by investors [47].
Analysts’ earnings forecast errors are gauged as
the differences (in absolute values) between the latest
analysts’ median consensus forecasts (MEDEST)
before the earnings announcements and the firms’
actual earnings per share scaled by stock prices [6].
We collect the data for earnings forecasts from
I/B/E/S. Prior studies in finance and accounting
support that analysts’ earnings forecast errors are
important for stock recommendations and firm stock
valuation [6, 43].
Analyst coverage is measured as the number (in
natural log) of stock analysts following or covering
the stock of the firm [5]. The higher the analyst
coverage of the firm, the more firm information can
be captured by analysts and investors.
Following prior accounting studies [26], we
measure and control for analyst expertise, which is
measured as the firm-specific experience of the
financial analysts working at the brokerage firm
(Chen and Matsumoto, 2006).
The data for institutional ownership are obtained
from the Thompson Financial CDA Spectrum
database of SEC 13F filings. This variable assesses
the percentages of the firm’s shares owned by
institutional owners relative to the total shares
outstanding of the firm [62].
Industry competition is measured as the inverse of
the Herfindahl concentration index, which is the sum
of squared market shares of the firms in the industry
derived from sales revenue, on the basis of Standard
Industrial Classification (SIC) codes [34].
Market environmental uncertainty is measured as
the uncertainty of the industry sales in the product
markets. We measure it with the standard deviation
of the previous five years of the sales revenue of the
industry to which the firm belongs [46].
generalized method of moments (GMM) for
estimations.
Endogeneity may exist in that firms with more
favorable analyst recommendations and higher stock
market value can afford more IT investments. To
account for this endogeneity bias, we use
instrumental variables with the lagged business
segment at t-2 and lagged industry IT investment
(excluding the firm, in line with the BLP approach to
dealing with endogemeity). To test the validity of
these instruments, we conducted the Hansen test.
GMM also employs the White heteroskedasticity and
autocorrelation robust covariance matrix.
In addition, to test the reverse causality direction
from analyst recommendations to IT investments, we
conducted the Granger causality test [29]. The results
confirmed the direction of influence from IT
investment to analyst recommendations across the
total IT investment and all specific IT investment
dimensions (smallest FGranger test = 12.371, p < 0.01),
except AIS. Furthermore, we tested various model
assumptions with the Jarque-Bera test, the RESET
test, the Durbin-Watson and White’s test, the
Davidson-MacKinnon test, and the Breusch-Pagan
test. None of the assumptions are violated in the
results. Finally, the multicollinearity problem is not a
serious threat because all variance inflation factor
results are less than five and the condition indices are
less than ten in our results.
5.1. Models Testing Moderated Mediation
Statistical testing moderated mediation requires a
comprehensive system of equations. Specifically, we
follow the widely accepted approach suggested by
Muller, Judd, and Yzerbyt [52]. The following
regression equations are utilized to test the moderated
mediation, where IT = the independent variable of IT
investment (total or specific IT dimension) for firm i
and time t, Recom = the mediator variable of analyst
stock recommendations, Value = the final dependent
variable of firm stock market value, and Mod = the
moderator variable of market environmental
uncertainty.
= + !" + #$ +
(3)
!" ∗ #$ + & '#*,-# + This equation gauges the moderation of the
overall effects of IT on firm stock market value.
.#/ = + !" + #$ +
(4)
!" ∗ #$ + & '#*,-# + Equation (4) assesses the moderation of IT on the
mediator of analyst recommendations.
= + !" + #$ +
!" ∗ #$ + .#/ + 0 .#/ ∗
(5)
#$ + & '#*,-# + Equation (5) can assess the moderation of both
the mediator of analyst recommendations on value
5. Empirical Model
Because the dataset is in panel structure, our
analyses can accommodate many biases. Specially, to
account for observable heterogeneity, we have
controlled for many multi-level (firm-, analyst-, and
industry-level)
covariates.
In
addition,
to
accommodate
firm-specific
unobservable
heterogeneity, endogeneity, heteroskedasticity, and
serial correlation in panel data, we employ the
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and the moderation of the residual effects of IT on
value after entering the mediator variable. Muller et
al. [52] suggest that in order to establish moderated
mediation, three conditions must be satisfied. First,
there should be a significant effect of IT on firm
stock market value ( ≠ 0). Second, the effects of
IT on the mediator significantly depend on the
moderator ( ≠ 0), and/or the effects of the
mediator on the final dependent variable significantly
depend on the moderator (0 ≠ 0). And third, the
residual effect of IT on firm stock market value is
significant ( ≠ 0), and controlling for the
mediator, is moderated [64].
R&D intensity
New product
announcements
Advertising
Firm size
ROA
ROA variability
Financial leverage
Dividend
Liquidity
Analyst coverage
Analyst forecast
errors
Analyst expertise
Inst. ownership
Ind. competition
R-squared
N
6. Results
are coefficients and standard errors (from the
bootstrapping) for the impact of independent
variables on mediators, while b and sb are coefficients
and standard errors for the impact of mediators on the
dependent variable. We find that Sobel test results are
significant (z value = 6.029, p < 0.01) for the indirect
mediation effects of analyst recommendations,
supporting H1.
.45***
.21**
Firm Stock
Market Value
0.97*
Panel A
0.43*
0.26***
0.19**
-0.18**
.00
0.63*
.02**
.18**
2.21***
-0.17
-0.00
.53
.02
1.88**
0.19***
0.31**
2.16***
-1.63**
0.00
0.15
0.38*
0.47**
-0.71**
-0.05
.61*
1.55**
-0.07
0.28
3,236
0.24**
2.15**
-0.31**
0.22
3,236
6.2. Moderating Role of IT Investment Type
H2 predicts that analyst recommendations have a
stronger mediating effect on firm stock market value
with enterprise IT investments (ERP and CRM) than
with functional IT investment (DSS, HR and AIS).
Table 3 Panel A results indicate that all enterprise IT
investments (ERP and CRM) affect recommendations
(p < 0.01). Entering the mediator of
recommendations in the model reduces the strength
of the effects of ERP and CRM-based IT investments
on value (from p < 0.01 to p < 0.10). Also, we find
that Sobel test results are significant (z value = 8.386
for ERP and 9.108 for CRM, p < 0.01), suggesting
indirect
mediation
effects
of
analyst
recommendations in channeling the effects of
enterprise IT investments (CRM and ERP) on firm
future stock market value. In contrast, the effects of
functional IT investment (DSS, HR and AIS) were
not significant on firm value (p>.10), although effects
of DSS and HR on analyst recommendations were
significant, thus not satisfying the conditions for the
mediating effects. These findings suggest that the
mediating role if indeed more effective for enterprise
IT investments (ERP and CRM) than functional IT
investment (DSS, HR and AIS), thereby supporting
H2.
zvalue ab / a 2 sb2 b 2 sa2 sa2 sb2 , where a and sa
IT
IT x environmental
uncertainty
Mediation Effects
Analyst Recom
Recom x env.
uncertainty
Controls
Env volatility
0.17***
Table
2:
IT
Investments,
Analyst
Recommendation and Firm Future Returns
6.1. Analyst Recommendations as a Mediator
between IT and Firm Market Value
In H1, we expect that analyst recommendations
mediate the associations between IT and firm stock
market value. Following Baron and Kenny [5] and
Zhao et al. [64], in order to establish mediation, IT
must affect analyst recommendations, and
recommendations must affect firm value. Table 2
Model 1 results indicate that IT significantly affects
recommendations (p < 0.01). Also, Model 2 results
indicate that IT significantly affects firm stock
market value (p < 0.05). Entering the mediator of
recommendations in the model reduces the strength
of the effects of IT on value (from p < 0.05 to p <
0.10). We also conducted the Sobel test extended by
the bootstrapping approach in order to gauge whether
the indirect mediation effects are statistically
significant [55]. The Sobel test model is:
Analyst
Recom
.02**
-0.52**
4099
CRM
CRM
ERP
ERP
IT
1.80**
IT x env.
0.72**
Uncertainty
Mediation Effects
Analyst Recom
Recom x env.
uncertainty
0.95*
1.95**
0.90*
0.44*
0.71**
0.45*
0.27***
0.31***
0.20**
0.19**
Panel B
IT
IT x env.
uncertainty
Mediation Effects
Analyst Recom
Recom x env.
uncertainty
DSS
DSS
HR
HR
n.s.
n.s.
n.s.
n.s.
n.s.
.31**
.10*
long-term debate on the variation of IT value by
investigating the value discovery role of stock
analyst. Different from investigating the business
value that IT investment can create, this study
challenges the invisible IT value creation process to
the public market and is the first few studies that
explore how the value of IT investment is discovered.
Strategy scholars have generally recognized the
importance of key stakeholders in understanding the
influence of firm actions [63], but IS research to date
yet has overlooked the value discovery process of
firms’ IT investment from them. By examining the
chain effect of stock analyst’s response between IT
investment and firm performance, we showed that the
value creation of IT investment is not an independent
process insides the firm. Rather, it is intertwined with
the active engagement of stock analysts who are
triggered by firms’ investment. While the argument
on how IT creates value has been the core research
question in IS field for decades, the current study
complements existing literature by examining, both
theoretically and empirically, the important value
discovery role of stock analyst that was missed to
explain the impact of IT investment on their market
value.
On a broader level, the study enlarges the scope
of IT value research and evokes attention for the
external process-oriented view on IT market value
research by adding a stakeholder perspective. With
respect to extant IS value literature which address on
internal ‘process-oriented’ capability factors, our
study contributes to previous knowledge by linking
IT investment to its market value on the analyst side.
Furthermore, by revealing that stock recommendation
may be an informational pathway through which IT
investment actions reaches the finance market, we
help explain why IT value might be over-estimated or
under-estimated [22, 23]. If analysts neglect or
overestimate firms’ IT investment, their assessments
of firm value will likely lead to a distorted
association between IT investment and firm value.
We provide evidence that the value discovery role of
stock analyst may partially account for the presence
or absence of the impact of IT investment on firm
value.
n.s.
n.s.
n.s.
n.s.
n.s.
Table 3: Variation Across IT Systems Types
6.3. Moderating Role of Environment Uncertainty
H3 expects that the mediating role of analyst
recommendations would be stronger in higher market
environment uncertainty. To test this moderated
mediation hypothesis, we rely on equations 3-5 [52].
Specifically, we find significant interaction effects of
environment uncertainty on the mediator of analyst
recommendations (p < 0.05), as well as significant
interaction effects of environment uncertainty on the
effect of analyst recommendation on firm value (p <
0.05). After controlling for the mediator, the residual
effect of IT on firm value is positively and
significantly moderated by environment uncertainty
(p < 0.05). Because the interaction effects are
positive in valence, the mediating role of analyst
recommendations between IT and value is indeed
stronger for firms with a higher (versus lower)
environment uncertainty, thus supporting H3.
7. Conclusions and Discussions
This research explores the value discover role of
stock analyst between firms’ IT investment and their
market value, a new way of understanding IT value
apart from extant IS value research mostly ignores.
We develop a set of hypotheses to explore how
market responds to firms’ IT investment by stock
analyst’s recommendation, which subsequently
influence firm market value. We validate the
hypotheses with 12-year longitudinal field data of
Fortune-1000 firms over 1996-2007. The dataset
contains three heterogeneous data sources including
survey data on firms’ IT investment, operations and
environment, stock analyst’s recommendation report
and firms’ stock price in stock market. The findings
show that, while the direct impact of firms’ IT
investment on firm market value exists, stock
analyst’ recommendation plays an important chain
effect in between. Furthermore, uncertain market
environments and IT system type significantly
moderate such relationship.
The theoretical implications of this study are
multifold. The first and foremost contribution of our
work is that we provide a new understanding of the
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