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E-BUSINESS VALUE CREATION FROM THE RBV OF the firm


E-BUSINESS VALUE CREATION FROM THE RBV OF the firm Pedro Soto-Acosta , Angel L. Mero?o-Cerdan Universidad de Murcia Abstract In recent years, scepticism about the value of e-business and information technology (IT) at the level of an individual firm has been renewed. In this sense, information systems researchers face pressure to answer the question of whether and how e-business creates value. To respond to this challenge, this paper develops a conceptual model, grounded in the resource-based theory, for assessing e-business value creation. This model posits three relationships: Internet resources and e-business value, Internet resources and e-business capabilities, and e-business capabilities and e-business value. To test hypotheses, a sample comprising 1,010 Spanish firms is employed. The results show that, as hypothesized, Internet resources per se are not positively associated with e-business value. Furthermore, although Internet resources are not positively related to e-business value, they are found to play a critical role in creating e-business capabilities. In addition, the results confirm that e-business capabilities are key drivers of e-business value. Keywords: e-Business, Value creation, Resource-based theory, Internet, Information technology 1 Introduction For more than a decade, researchers have been trying to quantify the benefits of information technology (IT) at the level of the individual firm. The results of these studies were varied and the term “productivity paradox” was coined to describe such findings. Nonetheless, recent studies have found positive and stronger linkages, and have attributed the productivity paradox to variation in methods and measures (Devaraj and Kohli, 2003). Research such as Henderson and Venkatraman’s (1999) argues that IT is evolving from its traditional back office role towards a strategic role, supporting new business strategies. However, recently much controversy about the value of IT has been created by assertions of Carr (2003), in his article “IT Doesn’t Matter”. Carr’s argument, in a few words, is that because every firm can purchase IT in the marketplace, because any advantage obtained by one company can easily be copied by another company, and because IT is now a commodity based on standards (such as the Internet) that all companies can freely use, IT is no longer a differentiating factor in organizational performance. What makes a resource truly strategic – what gives it the capacity to be the basis for a sustained competitive advantage - is not ubiquity but scarcity. Carr argues that no firm can use IT to achieve a competitive advantage over its competitors any more than it could with electricity, telephones, or other infrastructure. Therefore, Carr concludes, firms should reduce spending on IT, follow rather than lead IT in their industry, and avoid deploying IT in new ways. Most management information systems experts disagree with Carr’s assertions. The technology itself will rarely create superiority. For that reason, some research studies found that IT spending rarely correlates to superior financial results (Hoffman, 2002). However, IT can play an important role in developing superior business processes. Some researchers have described this in terms of IT capabilities and argue that IT capabilities can create uniqueness and provide organizations a competitive advantage (Bhardwaj, 2000, Bhatt and Grover, 2005; Mata et al., 1995; Santhanam and Hartono, 2003).

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Scepticism about the value of IT and e-business has been raised, due to the gap between IT investment – particularly on Internet technologies – and the widespread perception of the lack of value from e-business (Zhu and Kraemer, 2005). Thus, today information systems (IS) researchers face pressure to answer the question of whether and how e-business creates value. Although showing recent signs of advance, much of the existing e-business literature still relies, to a great extent, on case studies, anecdotes, and conceptual frameworks, with little empirical research directed to assessing the impact of IT on firm performance – especially in traditional companies (Brynjolfsson and Kahin, 2002). Case studies on firms such as eBay and Amazon show e-business can create business value, but there is a question as to whether the lessons learned from these “Internet giants” are more widely applicable. Another issue in the e-business literature is the lack of theory to guide empirical work (Wheler, 2002). To respond to these challenges, there is therefore a need for an empirically relevant but also theoretically rigorous framework. Consequently, this paper develops a conceptual model, grounded in the resource-based view (RBV) firms, in order to assess ebusiness value creation at the level of an individual firm. The analysis employs a large sample of companies from different industries for hypothesis testing. Moreover, although recent studies (Zhu, 2004; Zhu and Kraemer, 2005) have analyzed the relationship between ebusiness capabilities and firm performance, very little work has been undertaken to identify ebusiness resources and capabilities and study their separate influences on performance. Similarly, the relationship between e-business resources and capabilities has not been studied. The present study attempts to cover these gaps in the research. The paper consists of six sections and is structured as follows: The next section reviews the relevant literature. In Section 3, hypotheses and research models are specified. Following that, the methodology used for sample selection and data collection is discussed. Then, data analysis and results are examined. Finally, the paper ends with a discussion of research findings, limitations and concluding remarks. 2 LITERATURE REVIEW

2.1 The RBV: conceptualization of e-business capabilities The RBV has been used to answer one of the most extensively researched questions in the management strategy field, related to understanding the sources of sustained competitive advantages (Porter, 1985; Rumelt et al., 1991). At the same time, the RBV has become one of the standard theories to explain why firms in the same industry vary in performance over time (Hoopes et al. 2003). This suggests that the effects of individual, firm-specific resources on performance can be significant (Mahoney and Pandian, 1992). In this regard, the RBV is based on two underlying assertions: resource heterogeneity and resource immobility. Resources and capabilities possessed by competing firms are heterogeneously distributed and may be a source of competitive advantage when they are valuable, rare, difficult to imitate, and not substitutable by other resources (Barney, 1991; Schulze, 1992; Wernerfelt, 1984). At the same time, resources and capabilities are a source of sustained competitive advantage, that is, differences may be long lasting (resource immobility) when protected by barriers to imitation (Mahoney and Pandian, 1992) or isolating mechanisms (Rumelt 1984) such as timecompression diseconomies, historical uniqueness, embeddedness and causal ambiguity (Barney, 1991; Dierickx and Cool, 1989; Peteraf, 1993). The RBV generally tends to define resources broadly and include assets, infrastructure, skills, and so on. While resources serve as the basic units of analysis, firms create competitive advantage by assembling resources that work together to create organizational capabilities.

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Grant (1991) suggests that the capabilities of a firm are what it can do as a result of teams of resources working together. Teece et al. (1997) argued that capabilities cannot easily be bought; they must be built. Thus, building capabilities is not only a matter of combining resources; capabilities are rooted in processes and business routines. Also capabilities involve complex patterns of coordination between people and between people and other resources (Grant, 1991), and between an organization and other organizations. In this respect, Day (1994) describes capabilities as complex bundles of skills and accumulated knowledge, exercised through organizational processes, which enable firms to coordinate activities and make use of their assets. Day argues that capabilities and organizational processes are closely entwined, because capabilities enable the activities in a business process to be carried out. More recently, Makadok (2001) considers capability as a special type of resource. More specifically, he defines capability as an organizationally embedded non-transferable firmspecific resource whose purpose is to improve the productivity of the other resources possessed by the firm. For the purposes of the present study, the above definitions of capability permit the identification of three important characteristics: Capabilities are rooted in processes and business routines, because it is capability that enables the activities in a business process to be carried out. Capabilities are firm-specific, while an ordinary resource is not. Because of this embeddedness, ownership of a capability cannot easily be transferred from one organization to another. The primary purpose of a capability is to enhance the productivity of the other resources that the firm possesses. Extending the traditional notion of organizational capabilities to e-business, a firm’s ebusiness capability is defined here as its ability to mobilize and deploy Internet-based resources, in combination with or in the presence of other valued resources. E-business capabilities are firm-specific (or interfirm-specific) and rooted in processes and business routines. In the present study a distinction will be drawn between external and internal ebusiness capabilities. The former refers to the ability to mobilize Internet-based resources and other corporate resources with external business agents (e.g. supplier and customers), while the latter represents the ability to mobilize Internet-based resources and other corporate resources within a firm’s boundaries. 2.2 E-business resources and capabilities The RBV provides a solid foundation to differentiate between IT resources and IT capabilities and to study their separate influences on performance (Santhanam and Hartono, 2003). Based on this analysis, Bharadwaj (2000) suggested that if firms can combine IT related resources to create unique IT capabilities, they can improve their performance. IS researchers have followed this consideration of IT capability because competition may easily result in the duplication of investment in IT resources, and companies can purchase the same hardware and software to remove competitive advantage (Santhanam and Hartono, 2003). In this respect, IS research offers a useful distinction between IT resources and IT capabilities. The former is asset-based, while the latter comprises a mixture of assets formed around the productive use of IT. In general, IT resources are not difficult to imitate; physical technology is by itself typically imitable. If one firm can purchase these physical technologies and thereby implement some strategies, then other firms should also be able to purchase these technologies, and thus such tools should not be a source of competitive advantage (Barney, 1991). However, firms may

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obtain competitive advantages from exploiting their physical technology in a better (and/or different) way than other firms, even though competing firms do not vary in terms of the physical technology they possess. IT resources are necessary, but not a sufficient condition, for competitive advantages (Clemons and Row, 1991). IT resources rarely contribute directly to competitive advantage. Instead, they form part of a complex chain of assets (IS capabilities) that may lead to better performance. Thus, some researchers have described this in terms of IT capabilities and argue that IT capabilities can create uniqueness and provide organizations a competitive advantage (Bhardwaj, 2000, Bhatt and Grover, 2005; Mata et al., 1995; Ross et al., 1996; Santhanam and Hartono, 2003). For instance, Ross et al. (1996) provide illustrative case examples to underscore the idea that IT capabilities can provide competitive advantage and enhance the performance of firms. Within the e-business literature, although there is very limited research here, recent studies have found a significant positive relationship between e-business capabilities and firm performance (Zhu, 2004; Zhu and Kraemer, 2005). However, very little work has been undertaken to identify e-business resources and capabilities and study their separate influences on performance. Similarly, the relationship between e-business resources and capabilities has not been studied. Consequently, the present study seeks to demonstrate that Internet resources (considered as physical IT) are not responsible for e-business value. Instead, e-business capabilities are critical to firm value. That is, the combination of Internet resources and other valued corporate resources, and their integration in the organizational processes, may lead to better firm performance. 2.3 E-business value from a process approach The primary purpose of this paper is to determine how e-business creates value through the RBV. Thus, this research will test the RBV logic in the e-business context. Although much research using the RBV has focused on an aggregated dependent variable, namely, firm performance, this may not be the best way to test the RBV (Ray et al., 2004). For example, because firms can have competitive advantage in some business activities and competitive disadvantage in others, examining the relationship between resources and capabilities associated with different processes within a firm and its overall performance can lead to misleading conclusions. Ray et al. (2004) proposed examining the effectiveness of business processes as a way to test the RBV logic. Another issue is that some IT investments may provide benefits after a certain period but increase operating costs in the short term (Kauffman and Krieble, 1988). Thus, using firm performance at the macro level is meaningless and can again lead to misleading conclusions. Researchers suggest a processoriented approach to overcome these confounding problems. Kauffman and Weill (1989) hold that the locus of impact, that is, the business process, should be the primary level of analysis. Within the literature on e-business, recent research also suggests a perspective based on processes to overcome these problems (Subramaniam and Shaw, 2002). These arguments lead to the conclusion that a process approach should be used to explain the generation of ebusiness value within the RBV, and this is the approach adopted in the present study. The present research uses the effectiveness of online procurement to measure e-business value. The business value of this process is discussed below. E-procurement, or buying online, can potentially provide distinct value propositions to the firm. These come from the reduction of procurement and inventory costs, as well as strategic networks with suppliers that allow effective and efficient supply chain management (SCM). With regard to procurement costs, Kaplan and Sawhney (2002) indicated that buying in emarketplaces considerably reduces transaction costs. With regard to strategic links and SCM,

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Internet technologies can enhance SCM decision making by enabling the collection of realtime information, and access to and analysis of this data in order to facilitate collaboration between trading partners in a supply chain. In this sense, Frohlich and Westbrook (2002) showed the importance of linking customers and suppliers together in tightly integrated networks. As a result of e-procurement, the collection of real-time information on demand is possible and, more importantly, products and services are delivered quickly and reliably when and where they are needed (Frohlich, 2002). In sum, e-business value may lead to improved performance on the part of the firm in procurement. Although it could be argued that customers, suppliers and/or the firm’s wider value network can benefit from online procurement, this study focuses on analyzing ebusiness value creation at the level of an individual firm. 3 Development of hypotheses This section develops hypotheses for the present study, drawing on the existing information systems and e-business literature. Three relationships will be explored: Internet resources and e-business value, Internet resources and e-business capabilities, and e-business capabilities and e-business value (see Figure 1).
SC2 SC1 SC3 SC4

E-BUSINESS CAPABILITIES WITH SUPPLIERS IR1 INTERNET RESOURCES: Internet Infrastructure H2: + H4: +

IP1

IP2 IP3

IR2 IR3

H1: No relationship is expected

E-BUSINESS VALUE

H3: + IR4

H5: +

INTERNAL E-BUSINESS CAPABILITIES

IC4 IC1 IC2 IC3

Figure 1. E-business value creation (measurement model) 3.1 Internet resources and e-business value Barney (1991) argued that firms could obtain competitive advantages on the basis of corporate resources that are firm specific, valuable, rare, imperfectly imitable, and not strategically substitutable by other resources. IT resources are easy to duplicate, and, hence, IT resources per se do not provide competitive advantages (Santhanam and Hartono, 2003). Although IT infrastructure is argued to be valuable, it is not a source of competitive advantage (Bhatt y Grover, 2005). Thus, IT infrastructure will rarely lead to superior performance. Similarly, Internet resources – as defined above – are not difficult to imitate. In general, Internet technology is by itself imitable. If one firm can purchase certain Internet technologies and thereby implement some strategies, then other firms should also be able to purchase these technologies, and thus such tools should not be a source of competitive advantage. Furthermore, as the diffusion of the Internet continues, the ability of proprietary IT to be a source of competitive advantage continues to be eroded. These arguments suggest that Internet resources may not be responsible for value creation in e-business. Thus, the following hypothesis is proposed: Hypothesis 1: There is no relationship between Internet resources and e-business value

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3.2 Internet resources and e-business capabilities Although IS research has previously analysed the influence of IS resources and capabilities on firm performance, the research is fragmented and key gaps exist in the literature. Thus, despite research that has been undertaken to identify different resources and capabilities, and to analyze their direct effects on the performance of firms, the relationship between IT resources and IS capabilities has not been systematically studied. Only recent studies such as Ravichandran and Lertwongsatien’s (2005) offer a clear distinction between resources and capabilities. In this sense, Ravichandran and Lertwongsatien argue that examining the relationship between IS resources and IS capabilities can provide a better understanding of how resources could be deployed to develop capabilities. Within the area of e-business, recent studies have identified distinct e-business capabilities and studied their effect on performance (e.g. Zhu, 2004; Zhu and Kraemer, 2005). However, very little work has been undertaken to identify e-business resources and capabilities and study their separate influences on performance. Similarly, the relationship between e-business resources and capabilities has not been studied. Resources are the raw material in the development of capabilities. This relationship is implicit in the definition of capabilities as an organization’s ability to assemble, integrate, and deploy valued resources, usually, in combination (Amit and Shoemaker, 1993). Hence, the second and third hypotheses posit a positive relationship between Internet resources and e-business capabilities. Hypothesis 2: There is a positive relationship between Internet resources and external ebusiness capabilities with suppliers Hypothesis 3: There is a positive relationship between Internet resources and internal ebusiness capabilities 3.3 E-business capabilities and e-business value Engaging in IT investment is not a necessary nor sufficient condition for improving firm performance, since IT investments might be misused (Tallon et al., 2000). In this sense, IT assets cannot improve organizational performance if they are not used appropriately. However, when used appropriately IT is expected to create intermediary effects, such as IT being embedded in products and services, streamlined business processes, and improved decisions, which can be expected to have an influence on the performance of the firm (Ravichandran and Lertwongsatien, 2005). Grant (1991) and Makadok (1991) emphasize that while resources by themselves can serve as basic units of analysis, firms create competitive advantage by assembling these resources to create organizational capabilities. Makadok states that these firm-specific capabilities, embedded in organizational processes, provide economic returns because that firm is more effective than its rivals in deploying resources. IS researchers have adopted this capability logic of resources by arguing that competitors may easily duplicate investments in IT resources by purchasing the same hardware and software and, hence, IT resources per se do not provide competitive advantages. Rather, it is the manner in which firms leverage their IT investments to create unique capabilities that impact firm performance (Clemons and Row, 1991; Mata et al, 1995). Thus, it is expected that external and internal e-business capabilities have the potential to create business value. The following hypotheses incorporate these expectations: Hypothesis 4: There is a positive relationship between external e-business capabilities with suppliers and e-business value Hypothesis 5: There is a positive relationship between internal e-business capabilities and ebusiness value

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4

Methodology

4.1 Data The data source for the present study is the e-business W@tch survey 2003, an initiative launched by the European Commission for monitoring the adoption of IT and e-business activity. Telephone interviews with decision-makers in enterprises were conducted in March and November 2003. The decision-maker targeted by the survey was normally the person responsible for IT within the company, typically the IT manager. Alternatively, particularly in small enterprises without a separate IT unit, the managing director or owner was interviewed. The population considered in this study was the set of all enterprises which are active at the national territory of Spain and which have their primary business activity in one of ten sectors considered (see Table 1). The sample drawn was a random sample of companies from the respective sector population with the objective of fulfilling strata with respect to business size. A share of 10% of large companies (250+ employees), 30% of medium sized enterprises (50249 employees) and 25% of small enterprises (10-49 employees) was intended. The number of firms totalled 1,010. As shown in Table 1, 91.1% of firms were small and medium-sized enterprises (less than 250 employees) and each sector considered had a share of around 10% of the total sample. With regard to respondents’ titles, 54.4% were IS managers, nearly 20% were managing directors, and 12.1% were owners. The dataset was examined for potential bias in terms of the respondents’ titles. Since respondents included both IT managers and non-IT managers, one could argue that IT managers may overestimate e-business value. To test this possible bias, the sample was divided into two groups: IS managers (head of IT/DP and other IT senior managers) versus non-IS managers (owner, managing director, strategy development and others). One-way ANOVA was used to compare the means of factor scores between the two groups. No significant differences were found, suggesting that the role of the respondents did not cause any survey biases. Sample characteristics by sector, size and respondent Sector Name % N Number of employees % N Manufacture of textiles and leather 10 101 1-9 38.4 338 Manufacture of chemicals 9.9 100 10-49 25.8 261 Manufacture of electrical machinery 9.9 100 50-249 26.8 271 Manufacture of transport equipment 9.9 100 More than de 249 8,9 90 Crafts and Trade 10.7 108 Respondent title % N Retail 9.9 100 Owner/proprietor 12.1 122 Tourism 9.9 100 Managing director 19.6 198 Business services 9.9 100 Strategy development 1.9 19 Telecommunications & computer 9.9 100 Head of IT/DP 22 222 services 10 101 Other IT senior 32.4 327 Health and social services member Others 12.1 122 Table 1. Sample characteristics (N= 1,010). 4.2 Measures of variables The measurement model was developed after successive stages which included theoretical specification, and statistical testing and refinement as indicated by Straub (1989). Measurement items were introduced on the basis of a careful literature review. Confirmatory

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factor analysis (CFA) was used to test the constructs. Based on the CFA assessment, the measurement models were further refined and then fitted again. Constructs and associated indicators in the measurement model, as well as prior research support, are listed in the Appendix and discussed below. Internet resources construct. This construct represents the adoption of physical Internet technologies. In this sense, respondents were required to assess the presence of four Internet tools: website, Intranet, Extranet and LAN (local area network). External e-business capabilities. Consistent with the theoretical arguments made earlier, two constructs were developed. The former, e-business capabilities with suppliers, evaluates the use of online technologies for performing business activities with suppliers, while the latter refers to the use of online technologies for executing business activities with customers. Internal e-business capabilities. This construct represents the use of online technologies for supporting internal business processes. E-business value. As discussed earlier in section 2.3, the present research uses the effectiveness of e-procurement for measuring e-business value. That is, e-business value is assessed through the business impact of purchasing online. 4.3 Instrument validation CFA using AMOS 4.0 was conducted to assess empirically the constructs theorized. Multiple tests on construct validity and reliability were performed. Model fit was evaluated using the maximum likelihood (ML) method. The measurement properties are reported below (Table 2). Construct reliability. Construct reliability measures the degree to which measures are free from random error, and therefore yield consistent results. In the measurement model (Table 2), all constructs had a composite reliability over the cut-off of 0.70 (Straub, 1989), and also the average variance extracted for all exceeded the preferred level of 0.5 (Churchill, 1979). Content and construct validity. Content validity is the degree to which items in an instrument reflect the content universe to which the instrument will be generalized (Boudreau et al. 2001). This validity was verified by checking the meanings of indicators and by a careful literature review. Construct validity is the extent to which a construct measures the concepts that it purports to measure (Straub, 1989). It has two components: convergent and discriminant validity. Convergent validity assesses consistency across multiple constructs. After dropping insignificant items, all estimated standard loadings were significant (see Table 2), suggesting good convergent validity. To assess the discriminant validity – the extent to which different constructs diverge from one another – Forell and Larcker’s (1981) criterion, that average variance extracted for each construct should be greater than the squared correlation between constructs, was used. All constructs met this criterion.

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Construct Internet Resources: Internet Infrastructure e-Business Capabilities with Suppliers Internal e-Business Capabilities e-Business Value: Impact on Procurement

Indicators Loadings IR2 IR3 IR4 SC3 SC4 IC1 IC2 IC3 IP1 IP2 IP3 0.657 0.570 0.508 0.616 0.419 0.577 0.547 0.793 0.778 0.698 0.686

CV (tvalue) -5.470*** 5.307*** -3.593***

Reliability SCR = 0.882 AVE = 0.716 SCR = 0.915 AVE = 0.788 SCR = 0.783 AVE = 0.651 SCR = 0.844 AVE = 0.645

-6.537*** 6.877*** -8.601*** 8.499***

p<0.1*; p<0.05**; p<0.01*** Insignificant factors are dropped (IR1, SC1, SC2 and IC4) CV: Convergent validity; SCR: Scale composite reliability AVE: Average variance extracted; (--): Fixed items in the scale Table 2. Measurement Model: Factor loadings, reliability and validity Table 3 lists several goodness-of-fit statistics to assess how well specified models explain the observed data. The insignificant p-value (p = 0.107) for the chi-square statistics implied good absolute fit. The root mean square error of approximation (RMSEA) is the square root of the mean of the population discrepancy per degree of freedom. Small RMSEA values mean low residual variance and, therefore, a good fit in the model. RMSEA was below the cut-off value 0.08 suggested by Browne and Cudeck (1993). Five incremental fit indices were all above the preferred level of 0.9 (Gefen et al., 2000). In conclusion, the overall fit statistics, validity, and reliability measures allow the confirmation of the proposed model. Goodnesss-of-Fit Indices Chi-Square 49.087 p-value 0.107 RMSEA 0.032 Incremental Fit Normed Fit Index (NFI) 0.989 Relative Fit Index (RFI) 0.981 Incremental Fit Index (IFI) 0.997 Tucker-Lewis Index (TLI) 0.996 Comparative Fit Index (CFI) 0.997 Table 3. Measurement Model Fit indices 5 Empirical results E-business value creation hypotheses were tested using structural equation modelling. Figure 2 shows the model’s path coefficients. For e-business value, two of the three constructs –

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Internet resources, e-business capabilities with customers and internal e-business capabilities – have significant paths leading to the dependent construct. E-business capabilities with suppliers and internal e-business capabilities have significant positive paths, while Internet resources has a negative but statistically insignificant (p>0.10) coefficient, as hypothesized. Therefore, all hypotheses dealing with e-business value are supported (H1, H4 and H5). In addition, the model shows a significant positive linkage from Internet resources to e-business capabilities with customers (0.413*) and internal e-business capabilities (0.298***), hence supporting Hypotheses H2 and H3. Fit statistics confirmed that the measurement model provides a reasonable fit to the data (Chi-Square= 45.019, p= 0.120; NFI= 0.990; CFI= 0.998; RMSEA= 0.032; TLI= 0.996; IFI=0.998).
SC3 SC4

E-BUSINESS CAPABILITIES WITH SUPPLIERS 0.413* IR2 INTERNET RESOURCES: Internet Infrastructure 0.298*** -0.256 0.514*

IP1

IP2 IP3

IR3

E-BUSINESS VALUE

IR4

0.330**

INTERNAL E-BUSINESS CAPABILITIES

Note: p<0.1*; p<0.05**; p<0.01***

IC1

IC2

IC3

Figure 2. E-business value creation (structural model) 6 Conclusions, limitations and future research The present research seeks to explain how e-business creates value and is intended to offer results more widely applicable than studies of Internet leaders or IT industry companies. In this sense, this study attempts to offer an explanation to why there are cases where firms engage in e-business without deriving any benefits. To respond to these challenges, a conceptual model for assessing e-business value creation, grounded on the resource-based view (RBV) of the firm, was developed and tested on a large sample of Spanish firms from different sectors. The results showed, as hypothesized, that Internet resources are not positively related to ebusiness value. This finding is not surprising, since competitors may easily duplicate investments in IT resources by purchasing the same hardware and software, and hence IT resources per se do not provide better performance (Santhanam and Hartono, 2003). This can be explained through the RBV, because IT is not considered a resource that is difficult to imitate; IT is by itself typically imitable. This result supports the findings of recent research (Batt and Grover, 2005) that did no find evidence of a positive link between IT quality and firm performance. Similarly, Powell and Dent-Micallef (1997) showed that IT by itself cannot be a source of competitive advantage. Thus, our results confirm that Internet technology by itself will rarely create e-business value. Furthermore, results demonstrate that there is a positive relationship between Internet resources and e-business capabilities. This finding confirms Ravichandran and Lertwongsatien’s (2005) conclusions, who offered a clear distinction between resources and capabilities, and found a positive relationship between IS resources and capabilities. Within the area of e-business, recent studies have identified distinct e-business capabilities and studied their effect on performance (e.g. Zhu, 2004; Zhu and Kraemer, 2005). However, the relationship between e-business resources and capabilities has not been studied. Resources are

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the raw material in the development of capabilities. Thus, examining the relationship between IS resources and IS capabilities can provide a better understanding of how resources could be used for building capabilities (Ravichandran and Lertwongsatien, 2005). Thus, our findings suggest that although Internet resources are not positively related to e-business value, they play a critical role in creating e-business capabilities. Finally, the empirical results demonstrate that there is a positive relationship between ebusiness capabilities and e-business value. Our findings confirm the existing empirical literature. Bharadwaj (2000) and Santhanam and Hartono (2003) found that firms with superior IT capability do indeed exhibit superior firm performance. Ravichandran and Lertwongsatien (2005) showed that an organization’s ability to use IT to support its core competences depends on IS capabilities. Thus, even though competing firms do not vary in terms of the IT they possess, IS capabilities are rooted in processes and business routines and provide competitive advantage. In this sense, the results of the present study support the proposition that external and internal e-business capabilities are key drivers of e-business value. While the contributions of the present study are significant, it has some aspects which can be addressed in future research. First, the sample used was from Spain. It may be possible that the findings could be extrapolated to other countries, since economic and technological development in Spain is similar to other OECD Member countries. However, in future research, a sampling frame that combines firms from different countries could be used in order to provide a more international perspective on the subject. Second, the e-business value measure is subjective in the sense that it was based on Likert-scale responses provided by managers. Thus, it could also be interesting to include objective performance data for measuring e-business value. Third, this research takes a static, cross-sectional picture of capabilities, which makes it difficult to address the issue of how capabilities are created over years. A longitudinal study could enrich the findings. Fourth, in this study, two types of ebusiness capabilities are distinguished. In many survey studies in the IS literature, measurement instruments are used but there is not universal agreement on them. E-business research is still going through a process of developing measurement instruments, based on testing and refinement (Straub et al, 2002). In future, research should further validate and extend this typology.

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Appendix. Measures Constructs & Description Indicat. Internet Resources Does your company have a website? IR1 (Y/N)

Literature support

Grandon & Pearson (2004); Zhu et al. (2004); Zhu & Kraemer (2005)

IR2

Does your company use an Intranet? (Y/N) Kowtha & Choon (2001); Zhu et al. (2003); Zhu et al. (2004); Zhu & Kraemer (2005)

IR3 IR4 Does your company use an Extranet? (Y/N) Does your company use a LAN? (Y/N)

Kowtha & Choon (2001); Zhu et al. (2004); Zhu & Kraemer (2005) Zhu (2004); Zhu & Kraemer (2005) E-business capabilities with suppliers Angeles & Nath (2001); Brews & Tucci (2003, 2004); Wu et al. (2003)

SC1

Does your company use online technologies, other than e-mail, to exchange documents electronically with your suppliers? (Y/N) Do you place orders on special electronic marketplaces on the Internet? (Y/N) Do you order goods or services through access to the Extranet of a supplier? (Y/N)

SC2

Cagliano et al. (2003); Wu et al. (2003)

SC3

Cagliano et al. (2003); Wu et al. (2003)

SC4

Is your IT system integrated with that Brews & Tucci (2003, 2004); of a supplier for placing orders? (Y/N) Frohlich (2002); Frohlich & Westbrook (2002); Stratman & Roth (2002); Powell & Dent-Micallef (1997); Zhu et al. (2004)

Proceedings of European and Mediterranean Conference on Information Systems 2007 (EMCIS2007) June 24-26 2007, Polytechnic University of Valencia, Spain www.emcis.org

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Internal ebusiness capabilities Do you use online technologies to Gold et al. (2001); Wu et al. share documents between colleagues (2003) or to perform collaborative work in an online environment? (Y/N) Do you use online technologies to track working ours and production time? (Y/N) Do you use online technologies to support human resources management? (Y/N) When an online order comes, is the order fully integrated with the backend system? (Y/N) Brews & Tucci (2003, 2004);Pflughoeft et al. (2003); Powell & DentMicallef (1997)

IC1

IC2

Brews & Tucci (2003, 2004); Powell & Dent-Micallef (1997)

IC3

IC4

Stratman & Roth (2002); Zhu (2004); Zhu & Kraemer (2005) E-business value: Impact on What effect has online procurement on Wu et al. (2003); Zhu et al. Procurement (2004); Zhu & Kraemer the procurement costs? (1-5) (2005) What effect has online procurement on IP1 Kuan & Chau (2001); your relations to suppliers? (1-5) Lederer et al. (2001); Tallon et al. (2000); Teo y Pian (2003); Wu et al. (2003); IP2 What effect has online procurement on Zhu et al. (2004); Zhu & Kraemer (2005) the costs of logistics and inventory? (1-5) Wu et al. (2003); Zhu & Kraemer (2005) IP3 Note. Y/N, dummy variable; 1-5, five-point Likert-type scale. References
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Proceedings of European and Mediterranean Conference on Information Systems 2007 (EMCIS2007) June 24-26 2007, Polytechnic University of Valencia, Spain www.emcis.org


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