The other two dimensions of information systems strategic orientation are Product Development wider product range, new product, and product differentiation strategies and Market Developm
Trang 1systems in general support their business
strate-gies Thus, these small businesses are upgrading
their ways of competing that can lead to successful
national economic development (Porter, 2004)
These small businesses assess their competitive
positions in all four criteria of business
perfor-mance as strong
The factor analysis reveals the three
dimen-sions of information systems strategic orientation
7KH VWUDWHJLHV RI SURFHVV HI¿FLHQF\
LPSURYH-ment, cost reduction, quality service, and quality
product emerge as indicators of the information
systems strategic orientation dimension,
Cost-Quality Leadership The other two dimensions
of information systems strategic orientation are
Product Development (wider product range, new
product, and product differentiation strategies)
and Market Development (new market expansion
and intensive marketing strategies) These are in line with Ansoff’s matrix of strategy and Porter’s generic strategies
The defensiveness (Venketraman, 1989) is the predominant characteristic of the Cost-Qual-ity Leadership dimension The Proactiveness (Venketraman, 1989) is the predominant char-acteristic of the Product Development dimension and Aggressiveness (Venketraman, 1989) is the predominant characteristic of Market Develop-ment dimension The result presented in Table 5 was scrutinized to analyze the percentage of vari-ance in each information systems strategy score, H[SODLQHGE\WKHVHFRPPRQIDFWRUVDQGVSHFL¿F factors (Table 8) This analysis reveals that these three characteristics (common factors) mainly constitute the means (dimensions of strategic orientation) to achieve the formulated goals within the conditions set by the information systems resource in the external and internal domains These characteristics are held together by unique IDFWRUVWKDWDUHVSHFL¿FWRWKHFRQFHUQHGVWUDWHJLF JRDOV$IHZRIWKHVHVSHFL¿FIDFWRUVDUHMRLQWO\ VLJQL¿FDQW DQG PD\ LQFOXGH WKH FKDUDFWHULVWLFV
of Analysis, Futurity, Riskiness (Venketraman, 1989), and so forth As they are not common
to other strategies, these characteristics are not explicitly brought out by the factor analysis All these characteristics collectively describe the information systems strategic orientation The extraction of a single factor from multiple measures of business performance indicates that WKHIRXUGLIIHUHQWFULWHULDUHÀHFWWKHRYHUDOOEXVL-ness performance The factor score is an indica-tor of their business performance and is used as dependent variable in the regression analyses Multiple regression analysis provides insight into the relative importance of each dimension of information systems strategic orientation in the prediction of business performance The order
of importance is cost-quality leadership, product development and then market development The strategic orientation, like strategic alignment,
is a process and not an event The information
M ODEL C OMPONENT EXPORTERS
WITH WEB SITE
EXPORTERS WITHOUT WEB SITE
Independent Variables
Cost-Quality Leadership
5HJUHVVLRQ&RHI¿FLHQW
%HWD&RHI¿FLHQW
t value Sig
0.404 0.403 4.022
0.000
0.179 0.176 1.244 0.220 Product Development
5HJUHVVLRQ&RHI¿FLHQW
%HWD&RHI¿FLHQW
t value Sig
0.332 0.351 3.593
0.001
0.117 0.111 0.845 0.402 Market Development
5HJUHVVLRQ&RHI¿FLHQW
%HWD&RHI¿FLHQW
t value Sig
0.233 0.237 2.368
0.020
0.333 0.341 2.418
0.020
Model Fit
R 2 Adjusted R 2 ANOVA Sig
0.285 0.257
0.000
0.206 0.154
0.013
Table 7 Results of regression analysis—Web-site
owners and non-owners
Trang 2and industry oriented, whereas the strategy
align-ment is strategy independent and applicable to
all industries However, the strategic orientation
analysis has set the direction to the
measure-ment of alignmeasure-ment and its linkage with business
performance
The knowledge about the predictive value
of the information systems strategic orientation
is highly useful in understanding the business
value generating process of information systems
resource deployment in a given business setting
7KLVIDFLOLWDWHVWKH¿QHWXQLQJRIWKHLQIRUPDWLRQ
systems investment and adjusting the portfolio
of information systems applications by knowing
WKHHI¿FDF\RIDSDUWLFXODULQIRUPDWLRQV\VWHPV
strategy to attain certain ends within a particular
setting And strategic orientation as a process does
not normally lead to competitive convergence
(Porter, 2001)
Implication for Strategy Research
The major contribution of the present study is the
revelation of three core multifaceted dimensions
of information systems strategic orientation in
small business context This emphasizes that
small businesses explicitly indulge in information
systems strategic planning for business
perfor-mance management (Frolick & Ariyachandra,
2006) Future research could focus on small
business information systems strategic planning
and investigate their strategy making process
(Miller, 1987)
As the newer strategic management research
paradigm explicitly separate goals from strategy,
the information systems strategy could also be
viewed as means to attain certain ends within a
particular setting Empirically deriving
dimen-sions of strategic orientation a posteriori has
certain limitations (Venkatraman, 1989) A valid
operational measure could be developed
specify-LQJWKHLGHQWL¿HGGLPHQVLRQVDSULRUL
In net-enabled organizations (Straub,
Hoff-PDQ:HEHU 6WHLQ¿HOG VWUDWHJ\LVIDVW becoming a dynamic process of recreating and executing innovative options to gain and sustain competitive advantages (Teece, Pisano, Shuen, 1997) The insight gained through the present study into the relationship among core dimensions
of information systems strategic orientation in their prediction of business performance could
be used in assessing and choosing emerging and enabling information technologies (ET) Selecting (7LVWKH¿UVWVWDJHLQWKH1HWHQDEOHG%XVLQHVV Innovation Cycle (Wheeler, 2002) that asserts that choosing IT proceeds rather than aligns with business strategy in developing dynamic capabili-ties (Eisenhardt & Martin, 2000) to turn timely net-enabled business innovations into customer value (Chen, Chen, & Wu, 2005)
Future research studies could investigate whether the contingent effect of the Web presence
on the relationship between information systems strategic orientation and business performance is a direct one or intermediated by any other factor The capabilities of the Web site could also be examined
in detail to ascertain its role (Whinston & Geng, 2004) in determining the degree and character of association between information systems strategic orientation and business performance
Implications for E-Business Development
The Web presence strengthens the relationship between information systems strategic orienta-WLRQDQGEXVLQHVVSHUIRUPDQFHDVD³SURPRWLQJ´ YDULDEOH7KLVHPSKDVL]HVWKHVWUDWHJLFEHQH¿WVRI adoption of Web presence, one of the initial stages
of electronic business development The market development dimension of information systems VWUDWHJLFRULHQWDWLRQLVHTXDOO\VLJQL¿FDQWIRUH[-porters who have not yet adopted Web presence (Table 7) Even though their regression model explains only 15% of the variation in their business SHUIRUPDQFHWKHPRGHOUHPDLQVVLJQL¿FDQW
Trang 3It seems that their participation in the global
production networks, and the extent of trade
liberalization forced these exporters to adopt the
¿UVWVWDJHRIHOHFWURQLFEXVLQHVVGHYHORSPHQWYL]
e-mailing and Web information search as a means
of expanding their market The near universal
desire of business to gain advantages over their
competitors, in addition to extend their markets,
reach new markets, and protect existing markets,
LVSHUKDSVWKHPRVWVLJQL¿FDQWIRUFH *LEEV.UDH-mer, & Dedrick, 2003), driving these exporters
to move to the next stage of electronic business
development viz Web presence It appears that
Web presence creates information visibility
(Straub et al., 2002) forcing the small businesses
to improve their internal processes and strategic
positioning that in turn lead to superior business
performance
As the strategic planning in small businesses
is incremental in nature (Mintzberg, 1988), the
GHPRQVWUDWLRQRIWKHEHQH¿FLDOUHVXOWVIRUDGRSWHUV
will enable the small businesses to move forward
in the electronic business development Rogers
(1983) argues that change agents should recognize
their responsibility for the consequences of the
innovation they advocate Thus, the results of
the present study have practical implications to
government and nongovernmental organizations
that promote the diffusion of electronic business
adoption in small businesses
CONCLUSION
The small businesses are investing in
informa-tion and communicainforma-tion technologies to develop
information systems applications to support their
business strategy and thereby establish a
competi-tive advantage based on the distinccompeti-tive capability
created in their markets However, these small
EXVLQHVVHVVWUXJJOHWRDFKLHYHEXVLQHVVEHQH¿WV
from their information systems investments and
in particular to obtain a sustained competitive
advantage and superior business performance
To explore the relationship between the strategic orientation of these information systems and business performance, a study was designed The mail survey was conducted among 950 small businesses manufacturing and exporting knitwear apparels
The results reveal the three general patterns
of their realized information systems strategies viz cost-quality leadership, product development, and market development These dimensions of information systems strategic orientation have strong positive relationship with their business performance The consequences of their adop-tion of Web presence promote the degree of the linkage between information systems orienta-tion and their business performance The study demonstrates the business value of information systems investment and adoption of initial stages
of electronic business development
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Trang 7Chapter 6.5
E-CRM and Managerial Discretion
Tim Coltman
University of Wollongong, Australia
Sara Dolnicar
University of Wollongong, Australia
ABSTRACT
Most sectors of industry, commerce, and
govern-ment have reported variation in the performance
payoff from electronic customer relationship
management (e-CRM) In this paper we build
on surprisingly sparse literature regarding the
importance of managerial discretion to show that
the heterogeneity of beliefs held by managers about
e-CRM execution matter when explaining e-CRM
success Drawing on a data sample comprising 50
interviews and 293 survey responses we utilise
VHJPHQWDWLRQWHFKQLTXHVWRLGHQWLI\VLJQL¿FDQW
differences in managerial beliefs and then
as-sociate these belief segments with e-CRM
per-formance Results indicate that (1) three distinct
W\SHVRIPDQDJHUVFDQEHLGHQWL¿HGEDVHGRQWKH
heterogeneity of their e-CRM beliefs: mindfully optimistic, mindfully realistic, and mindfully pessimistic; (2) that there is far less homogene-LW\DWWKHLQGLYLGXDO¿UPOHYHOWKDQLVQRUPDOO\ assumed in the literature; (3) that heterogeneity
in managerial beliefs is systematically associated with organisational performance; and (4) these results serve to remind practitioners that e-CRM performance is dependent upon the right balance between managerial optimism and realism
INTRODUCTION
A major focus of marketing theory and practice has attributed variation in the degree of business success to the importance of the customer and the
Trang 8competitive advantages associated with a market
orientation (Rust, Zeithaml, & Lemon, 2000) One
YLHZRIPDUNHWRULHQWDWLRQGH¿QHVLWDVWKHDELOLW\
to systematically gather and analyse customer
and competitor information, to share this market
knowledge, and then to use this knowledge to
guide strategy recognition, understanding,
cre-DWLRQVHOHFWLRQLPSOHPHQWDWLRQDQGPRGL¿FDWLRQ
(Hunt & Morgan, 1995) It should also come as
no surprise that many marketers have turned to
information technology—in particular CRM—as
a way to support customer-oriented thinking,
customer analysis, and understanding
Enthralled by possibilities to deliver rich
information regarding buyer behaviour to sales
representatives, corporate investment in CRM
technology has grown at a compound annual rate
of 11.5% (Forrester Research, 2002) Reports of a
positive link between CRM uptake and improved
¿UP SHUIRUPDQFH KDYH EHHQ OHVV HQFRXUDJLQJ
For example, the Gartner Group, a research and
DGYLVRU\¿UP claims that close to 50% of all CRM
projects fail to meet expectations (The Australian,
8th July, 2003) Additionally, an InfoWorld survey
RI FKLHI WHFKQRORJ\ RI¿FHUV ,QIR:RUOG
IRXQGWKDWFORVHWRRIFKLHIWHFKQRORJ\RI¿FHUV
VDLGWKDW&50ZDVRQHRIWKHPRVW³RYHUK\SHG´
technologies they had seen A follow-up survey
of information technology (IT) executives found
that 43% of large companies that have deployed
CRM still believe that it deserves the bad press
(InfoWorld, 2003)
In contrast to the aforementioned industry
survey reports, the recent academic literature
DSSHDUVWRFRQ¿UPWKDW&50SURJUDPVHQKDQFH
¿UPSHUIRUPDQFH)RULQVWDQFHLQDVSHFLDOVHF-tion in the Journal of Marketing eight of the ten
papers published—conducted in a wide variety
of industry settings—came to this conclusion
(Boulding, Staelin, Ehret, & Johnston, 2005)
As a whole however, CRM is a neglected area
RIUHVHDUFKZKHUH³IXUWKHUHIIRUWVWRDGGUHVVLWV
mobilization and alignment are not only warranted
but desperately needed” (Zablah, Bellenger, & Johnston, 2003, p 116)
One of the problems with the way CRM and performance has been measured is that the term often means different things to different people, creating confusion and uncertainty For example,
in a series of interviews with executives, Payne and Frow (2005) found that to some, CRM meant direct mail, a loyalty scheme, help desk, and call centre Whereas, others envisioned a data warehouse, data mining, e-commerce solutions,
or databases for sales force automation To al-OHYLDWH WKLV SUREOHP ZH IRFXV VSHFL¿FDOO\ RQ H&50SURJUDPVDVGH¿QHGLQD6$6,QVWLWXWH white paper (2000):
the creation of knowledge from process automa-tion and the collecautoma-tion, synthesis and delivery of data derived from the Internet and information technology (IT) based interactions between the company and its customers/channel partners.” 7KLV GH¿QLWLRQ FDSWXUHV WZR LPSRUWDQW DVSHFWV
of e-CRM: (1) IT infrastructure, and (2) e-intel-ligence capability Modern IT such as relational databases, data warehousing, data mining, and Internet delivery are a feature of e-CRM programs that customise and enhance personal relationships with customer and suppliers However, alone IT LVDQLQVXI¿FLHQWVRXUFHRIFRPSHWLWLYHDGYDQWDJH (Carr, 2003) Rather, competitive advantages arise from the interpretation of data or what we refer
to as e-intelligence in this study 1
For many managers, e-CRM creates an envi-ronment that is unfamiliar Whenever decision makers face unfamiliar territory there is greater opportunity for managerial discretion to be seen DVUHOHYDQWDQGSUDFWLFDOO\LPSRUWDQWWRWKH¿QDO payoff Hambrick and Finkelstein (1987) were the
¿UVWWRLQWURGXFHDQGHODERUDWHRQWKHFRQFHSWRI managerial discretion as a way to reconcile polar YLHZVDERXWKRZPXFKLQÀXHQFHH[HFXWLYHVDQG senior managers have on organisational outcomes
Trang 9'H¿QHGDVWKH³ODWLWXGHRIDFWLRQ´WKHLUSURSRVL-tion was that senior decision makers vary widely
in how much discretion they have Managerial
discretion is not only theoretically important in
its own right, but also potentially important to the
complex decision making that accompanies
e-CRM investment programs Yet, it is by no means
clear that modern managers always engage in a
deliberate and considered way when addressing
issues of whether, when, and how to invest in IT
programs (Swanson & Ramiller, 1997; Swanson
& Wang, 2005)
In this article we begin to explore this issue
by investigating the effect of individual
determi-nants of managerial discretion on organisational
performance in the context of e-CRM In doing
so, we extend present work in two directions:
(1) we propose a new dimension of individual
determinants of managerial discretion which
have so far not been used, namely, managerial
beliefs In this particular study, it is investigated
whether managerial beliefs towards e-CRM are
associated with organisational performance; (2)
we introduce heterogeneity into the discussion
of individual determinants of managerial
discre-tion While accounting for heterogeneity among
individuals is a common procedure in consumer
behaviour studies, heterogeneity among managers
with respect to individual determinants of
mana-gerial discretion has so far been neglected We
hypothesise that managers with different patterns
RI EHOLHIV UHJDUGLQJ H&50 FDQ EH LGHQWL¿HG
and that segment membership is associated with
e-CRM performance
7KHDUWLFOHLVVWUXFWXUHGDVIROORZV ¿UVWZH
direct our attention towards the determinants of
managerial discretion and the link to mindful
(and mindless) behaviour Next, we describe the
empirical setting, along with a discussion of the
sample and the clustering method used Lastly, we
discuss our results and offer suggestions to
manag-ers seeking to invest in e-CRM programs
Conceptual Foundations
0DQDJHULDO GLVFUHWLRQ LV D FKDOOHQJLQJ ¿HOG RI research As Hambrick and Finkelstein (1987) argue, discretion is determined by three sets of factors: (1) characteristics of an organisation’s
environment, in particular its industry; (2) the
degree to which the organisation itself is amenable
to execution and action; and (3) the degree to
which the individual executive is able to envision
a new course of action Moreover, each of these categories holds multiple determinants of discre-tion, which do not necessarily co-vary (Hambrick
& Abrahamson 1995) So, if a researcher wishes
to empirically measure managerial discretion as
it applies to e-CRM programs, it is not clear how much weight should be given to environmental/ industry factors posed by Hambrick and Finkel-stein (1987), or organisational factors (Hannan & Freeman, 1977) or individual forces (Swanson & Ramiller, 1997)
Environmental Determinants of Managerial Discretion
Environments afford managerial discretion in dif-ferent ways with some supporting greater variety and change than others In some environments managers have a wide array of potential courses
of action to experiment with programs such as e-CRM In other environments, few options exist Managers are literally constrained by external forces, or there is relatively little ambiguity in the business, so only a narrow range of options
is plausible among the executive (Thompson, 1967)
+DPEULFN DQG )LQNHOVWHLQ VSHFL¿HG seven industry level factors that determine mana-gerial discretion: (1) product differentiability, (2) market growth, (3) industry structure, (4) demand instability, (5) quasi-legal constraints, (6) power-ful outside forces, and (7) capital intensity In a follow-up empirical investigation, Finkelstein and Hambrick (1990) used qualitative assessments to
Trang 10show that the top management team was strongly
associated with strategic persistence and
confor-mity to industry norms in a low-discretion industry
(natural gas distribution) than was the case in a
high-discretion industry (computers)
However, this type of qualitative approach
to assessing industry discretion is very limiting
because it requires one to examine industries that
are unambiguous in their degrees of discretion In
reality, this is rarely the case and industry
discre-tion is not best thought of as a unitary construct
(Hambrick & Abrahamson, 1995)
Organisational Determinants of
Managerial Discretion
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of the game” by which players, both
individu-als and organisations, interact in exchange ties,
be they social or economic (Carson, Devinney,
Dowling, & John, 1999) From this perspective,
neo-institutionalism recognises the importance
of embedded organisational complexity (i.e.,
rules of the game) and argues that hypothetically
ideal strategic orientations can be fundamentally
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inertial tendencies of organisations and about how
inertia precludes choice (Hannan & Freeman,
1977; Tushman & Romanelli, 1985) The major
forces that are thought to create inertia, and in
turn, reduce executive discretions include: (1)
size, (2) age, (3) culture, (4) capital intensity, (5)
resource availability, and (6) internal political
conditions (Hambrick & Finkelstein, 1987) This
line of thinking is well developed by Carson et
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therefore, are not feasible alternatives
It is generally argued, at least among population
ecology and institutional scholars, that
environ-ment and organisation characteristics generally
inhibit an organisation’s ability to consider change
and therefore limit the extent of managerial
discre-tion However, managerial discretion is not just
LQÀXHQFHGE\HQYLURQPHQWDODQGRUJDQLVDWLRQDO factors, but by the executive himself or herself
Individual Determinants of Managerial Discretion
By virtue of their personal characteristics, execu-tives and senior managers differ in the degree
to which they generate and consider different investment programs (Hambrick & Finkelstein, 1987) The relevant characteristics previously examined include: (1) aspiration levels, (2) level
of commitment, (3) tolerance of ambiguity, (4) cognitive complexity, (5) political acumen, and (6) location of power base This work has largely been driven by a vision of decision making that
is drawn from the logic of appropriateness based
on organisational rules and practices (March, 1991)
An interesting twist to the research on indi-vidual discretion is the reality that because most managers are highly optimistic most of the time, there is a tendency to take unnecessary risks Although this over optimism can be traced to many sources, one of the most powerful is the tendency by individuals to exaggerate their own talents—to believe that they are above average in their ability to implement change programs (La-vallo, 2004) Furthermore, bandwaging behaviour RIWKH³PHWRR´YDULHW\ZKHUHLQGLYLGXDOVVHHN
to replicate moves by competitors has also been shown to motivate prior investment in innovation (Abrahamson, 1991)
2QH RI WKH PRVW FRQVLVWHQW ¿QGLQJV HPHUJ-ing from organisational decision research is that people have very little time for problem solving and when they do undertake these activities they tend to display considerable irrationality (Brunsson, 1985) They make inferential errors, create myths to account for uncertainty, and are resistant to feedback (March, 1994) In other words, scant reasoning may characterise IT-related investments such as e-CRM programs—with VXEVHTXHQW LPSOLFDWLRQV IRU ¿UP SHUIRUPDQFH
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