1774 Exploring Relationship between Information Systems Strategic Orientation and Small Business systems 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 IDFW RUV W KDW D U H V SH F L ¿FWRW KHFRQF H U QH GVW U DWHJ LF 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 MODEL COMPONENT 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 1775 Exploring Relationship between Information Systems Strategic Orientation and Small Business V\VWHPVVWUDWHJLFRULHQWDWLRQLVVWUDWHJ\VSHFL¿F and 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 alignment 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. 7 K LVIDFLO LW DWHVW KH¿QH W X Q L QJRIW KHLQ IRU PDW LRQ 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:HEHU6WHLQ¿HOGVWUDWHJ\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 1776 Exploring Relationship between Information Systems Strategic Orientation and Small Business It 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, L V S H U K D S V W KH P R V W VL J Q L ¿ F D Q W IR U F H * L E E V . U D H - 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 G H P R Q V W U D W L R Q RI W K H E H Q H ¿ F L D OU H V X OW V I R U D GR S W H U V will enable the small businesses to move forward in the electronic business development. Rogers (19 83) a r g u e s t h a t c h a n g e a g e n t s s h ou l d r e c og n i z e 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 communication technologies to develop information systems applications to support their business strategy and thereby establish a competi- tive advantage based on the distinctive 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. 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Chapter 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 1781 E-CRM competitive 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 KDYHEHHQ OHVV HQFRXUDJLQJ For example, the Gartner Group, a research and DGYLVRU\¿UPclaims 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 collection, 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. 'H¿QHGDVWKH³ODWLWXGHRIDFWLRQ´WKHLUSURSRVL- 1782 E-CRM 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). +DPEULFNDQG)LQNHOVWHLQVSHFL¿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 1783 E-CRM show 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 1HRLQVWLWXWLRQDOWKHRU\GLUHFWVXVWRWKH³UXOHV 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 ÀDZHG,QGHHGPXFKKDVEHHQZULWWHQDERXWWKH 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 DO ZKR WKHRULVH WKDW ¿UVW EHVW VWUDWHJLF RULHQWDWLRQVDUHRIWHQIXQGDPHQWDOO\ÀDZHGDQG 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 v i r t ue of t hei r p er son al c ha ra ct er i st ics, exec u- 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). 2QHRIWKHPRVWFRQVLVWHQW¿QGLQJVHPHUJ- 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 . 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. 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. process automa- tion and the collection, synthesis and delivery of data derived from the Internet and information technology (IT) based interactions between the company and its customers/channel