Process uncertainty

Process uncertainty refers to the dynamisms and complexity of the procurement process and of the underlying products (Bensaou and Venkatraman 1995, Choudhury 1997, Subramaniam and Shaw 2002, 2004; Premkumar et al. 2005).Firm 2 has the lowest process uncertainty of all the other three firms due to its simple order management process, and special but simple products (i.e. labeling materials). More details can be referred to Table 3c.

Table 3c. Cross-case analysis results: Process uncertainty

Model variables Firm 1 Firm 2 Firm 3 Firm 4

Dynamics of process Medium (Fulfill order, return process)

Low (Fulfill order) High (Fulfill order, contact extra support person)

High (Fulfill order, coordinate hub delivery)

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The major tasks of the order management process are diverse among 4 cases. For firm 1, the sales representatives are responsible of fulfilling order, coordinating and contacting RD personnel of both sides, and managing the return of defective items. In contrast, firm 2’s sales people only need to manage order fulfillment and trace the design drawing in case of missing, since their RD design and reverse logistics is not as complicated as firm 1. On the other hand, the sales people of firm 3 need to spend extra efforts to manage order fulfillment. They must get contact with the procurement executives of the focal firm and their assistants there to get shipping information. Accordingly, most of their working time is spent on PO maintenance. For firm 4, the sales people pour great efforts in fulfilling order as well. However, contact subjects are slightly different. They need to coordinate with Hub personnel besides the procurement executives of the focal firm to ensure the fulfillment is done. In their opinion, the Hub personnel are too passive and insufficient in cooperation, resulting in a very poor exceptions handling. At most of the time, they still need to strive alone.

Dynamics of product High (Change by every module in the

In firm 1’s case, casting materials are special materials which are incompatibly across different modules. Namely, a cast only corresponds to a single NB module. Before providing such product, firm 1 need to discuss the form, the operation, the material, the function and the structure of a cast. On the contrary, firm 2, firm 3 and firm 4 have no cooperative R&D problems, given that labels are simple materials and cables as well as passive components are relatively standard materials. However, firm 2 face more frequent product change, for the context of labels is set along with the specifications of separate modules, and the specifications sometimes change with the requirements of customers or the upgrades of NB versions.

Complexity of product High (Special and dedicated material) The casting materials produced by firm 1 belong to dedicated/special materials and must go through several stages before commercial production (Lead time: 1 month; Duration of a batch production: 3~5 days). The product complexity is relatively high compared with the other three. The labeling materials provided by firm 2 are part of dedicated materials, but there is no complicated R&D or material recognition (Lead time: 1 week; Duration of a batch production: 1 day). The cable materials supplied by firm 3 are standard materials with medium technology complexity (Lead time: 1 month; Duration of a batch: 1~2 days). Firm 4 produces passive components, which are standard materials with low technology complexity (Lead time: 1~2 months; Duration of a batch production: 3days).

Process uncertainty: Medium-high Low Medium Low-medium

4.3.4 Know-how/Knowledge

Technical IT skills and managerial IT skills are used to measure the knowledge and know/how required for EP use (Lee et al. 1995, Mata et al. 1995, Yu et al. 2003). Firm 4 have the highest technical and managerial skills for its various IT connections and abundant IT implementation experience. Table 3d summarizes the result.

Table 3d. Cross-case analysis results: Knowledge/Know-how

Model variables Firm 1 Firm 2 Firm 3 Firm 4

Technical skills Medium (No difficulty with Since all these four companies run the EP system smoothly, we may say that all of them have certain degree of IT capabilities. To discuss their technical skills further, we looked into their transactions with other firms. No surprisingly, they do business with others via various EP systems and some of the systems require higher level of technical skills. For instance, firm 4 has also built EDI and RosettaNet connections.

Managerial skills Low (Not shown) Medium-low (coordination skills) Firm 1 didn’t suffer much environmental uncertainty, so they did not show many managerial skills about current procurement practice. Firm 2 and firm 3 show apparent coordination skills in the form of their frequent interaction with the executives of the focal firm. To support delivery and transportation, firm 3 even sent an extra assistant to the focal firm’s warehouse. As for firm 4, it spent great effort to coordinate procurement activity as well. In order to avoid

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the due date delay firm 4 proposed a solution which directly linked the EP to their organizational system via EDI to maintain the status of order automatically. Though the proposition was denied eventually, there is no doubt that firm 4 have sufficient ability and willingness to improve the performance of procurement activities.

Know-how/Knowledge Medium-low Medium Medium High

4.4.5 Performance

The performance of EP can be measured from several different perspectives. Mukhopadhyay and Kekre (2002) proposed a two-stage model of benefits in which IT are viewed as creating direct, first-order benefits, which in turn generate indirect, second-order benefits. According to them, the first-order benefits include: (a) direct strategic benefits typically in terms of sales gains, and (b) direct operational benefits typically in terms of process-based operational measures, such as the improvement of order-processing cycle and timeliness of payments. The second-order benefits are indirect strategic benefits that are influenced by direct benefits created by IT and accrue over an extended period of time. In our paper, we only consider the first-order benefits. Of all the case companies, firm 1 had the least complaints about the EP system and mentioned the most operational benefits related with time and error reduction. The analysis can be found in Table 3e.

Table 3e. Cross-case analysis results: EP Performance

Model variables Firm 1 Firm 2 Firm 3 Firm 4

Operational benefits High (Great benefits in term of time and

Operational benefits such as time and error reductions related to payments and order confirmation and increasing accuracy of order processing are mentioned in firm 1, firm 2, and firm 3 in some extent. Given that the EP system can transform PO into advanced shipping notice (ASN) automatically, the inconsistencies between PO and shipping notice mitigate greatly. Despite these benefits, firm 2 and firm 3 mentioned more or less that current system fails to support their procurement practices, especially in firm3’s case. For firm 4, their sales didn’t think the EP brings much convenience to their daily operation. Instead, they complained most information provided by the system is inaccurate and out of date. And unfortunately, because of Hub delivery instruction, ASN is useless in firm 4’s case.

Performance: High Medium Low-medium Low

5. Discussion

A simple bar chat shown as following figure 3 summarizes the case analysis. As the diagram indicates, firm 1 and firm 2 belong to a low level of environmental uncertainty, while firm 3 and firm 4 belong to a high level of environment uncertainty. The need of accurate and timely forecasts and shortage information are emphasized in the cases of firm 3 and firm 4 since they have to deal with greater dynamics of demand and supply. However, the forecasts may come from various sources. EP systems which can help integrate such information from different sources should be especially beneficial to suppliers like firm 3 and firm 4.

Figure 3 also shows that partnership uncertainty increases progressively from firm 1 to firm 4. It seems that the reciprocal investment does not impact the performance much in our cases since the level of reciprocal investment is quite indiscriminate in all cases. We find that firm 2, firm 3, and firm 4 suspect that the OEM doesn’t conform to its pre-determined order allocation. These

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suspicions lead to low perceived benefits of the current EP system and give rise to more information need to handle the perception of risk associated with partners’ opportunistic behavior.

The situation of process uncertainty is more complicated. In previous literature, as we have seen, the complexity of procurement process is highly related to the products upon them. However, we find that they are negatively related in these four cases. Specifically, the less specific and dynamic the materials are, the more suppliers competed in the market. Therefore, each supplier has smaller power and is asked to follow the rule made by the buyer. Suppliers in such circumstance need to pay additional efforts to process the transaction successfully. In fact, firm1, firm3 and firm4 do express that the current EP system can’t support them to process order fulfillments successfully.

Environment Uncertainty

Partnership Uncertainty

Process Uncertainty

Knowledge Performance

Firm 1 Firm 2 Firm 3 Firm 4

Figure 3. Case results of the four dimensions and performance

Finally, the level of knowledge skills is higher in firm3 and firm4. Firm 4 who shows the most mature capability in both IT and managerial skills has better know-how in technology. But for other suppliers, they do not have such strong knowledge bases as firm 4. Besides, the OEM, in our case, spends few efforts training the suppliers using the EP systems. Most of the suppliers admit that they grope for the system’s function on their own. We also find that even with lower knowledge skills, firm 1 and firm 2 still view the current web-based EP system simple enough for them to get familiar in the short run.

In summary, these four suppliers can be roughly divided into two groups. Firm 1 and firm2 have relatively lower external uncertainty and higher internal uncertainty. Firm 3 and firm 4 are in the contrary. Our case study shows that the low integrated web-based EP system drives better performance in suppliers like firm 1 and firm 2, which is consistent with our propositions.

Nevertheless, firm 3 and firm 4 show sufficient capability and willingness to reduce their

uncertainties and improve performance eventually. Though a simple basic EP system can not live up to expected benefits in complex and dynamic environment, a powerful highly integrated EP system can not fit all suppliers neither. Firms may prefer to maintain a unique EP system due to cost consideration and other concerns. However, we argue that companies should align their EP with different suppliers just like they provide several versions of their products for different customers to get maximum profits. Fit between business environment and technology can produce win-win situation and best profits to both buyer and sellers.

High

Medium

Low

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6. Conclusion

Through the empirically case study, we find the firms’ external and internal factors can affect the performance of EP. That is, EP usage in the form of low-integrated system may lead to greater performance under lower environment, partnership, or process uncertainty, and lives up to more benefit under lower knowledge skills. We also observe that lack of fit between procurement

practices and EP system produces extra burdens and costs to companies. Such costs are reflected in the performance of both buyer side and supplier side. Therefore, companies should align their EP with different trading partners to get maximum efficiency and benefits. The IT context of this case study focuses on low-integrated systems which are the most popular means of e-commerce

transaction in Taiwan manufacturing industry and leaves highly-integrated EP an unsettled subject.

In the future we can design more quantifiable measures to further validate the result derived from the case study.

7. References

1. Baron, J.P., Shaw, M.J., and Bailey, Jr., A.D. "Web-based e-catalog systems in B2B procurement,"

Communications of the ACM (43:5), 2000, pp. 93-100.

2. Bensaou, M., and Venkatraman, N. "Configurations of interorganizational relationship: A comparison between U.S. and Japanese automakers," Management Science (41:9), 1995, pp. 1471-1492.

3. Chan, J.K.Y., and Lee, M.K.O. "SME e-procurement adoption in Hong Kong—The roles of power, trust and value," The 36th Hawaii International Conference on System Sciences (HICSS'03), Big Island, HI, 2003, pp. 179-188

4. Chen, H., Themistocleous, M., and Chiu, K.H. "Approaches to supply chain integration followed by SMEs: An exploratory case study," The 10th Americas Conference on Information Systems (AMCIS2005), New York, NY, 2004, pp. 2610-2620.

5. De Boer, L., Harink, J., and Heijboer, G. "A conceptual model for assessing the impact of electronic procurement," European Journal of Purchasing & Supply Management (8) 2002, pp. 25-33

6. Duncan, R.B. "Characteristics of organizational environments and perceived environmental uncertainty,"

Administrative Science Quarterly (17:3), 1972, pp. 313-327.

7. Favre, D. and Brooks, J. “E-sourcing: procurement’s leading edge,” ASCET (4), 2002, pp. 74-76.

8. Gebauer, J., and Segev, A. "Assessing internet-based procurement to support the virtual enterprise,"

CALS Expo International and 21st Century Commerce: Global Business Solutions for the New Millennium, Long Beach, CA, 1998

9. Grant, R.M. "Prospering in dynamically-competitive environment: Organizational capability as knowledge integration," Organizational Science (7:4), 1996, pp. 375-387.

10. Gribbins, M.L., Subramaniam, C., and Shaw, M.J. "The impact of process and technology factors on user's assessment of the fit of e-procurement with the procurement process," The 3rd Workshop on E-Business (WeB2004), Washington, DC, 2004.

11. James I. Cash, J., and Konsynski, B.R. "IS redraws competitive boundaries," Harvard Business Review, 1985, pp. 134-142.

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12. Kalakota, R., and Robinson, M. E-Business: Roadmap for Success Addison-Wesley, MA, 1999

13. Lee, D.M.S., Trauth, E.M., and Farwell, D. "Critical skills and knowledge requirements of IS professionals: A joint academic/industry investigation," MIS Quarterly (19:3), 1995, pp. 313-340.

14. Luftman, J., and Brier, T. "Achieving and sustaining business-IT alignment," California Management Review (42:1), 1999, pp. 109-122.

15. Mata, F.J., Fuerst, W.L., and Barney, J.B. "Information technology and sustained competitive advantage:

A resource-based analysis," MIS Quarterly (19:4), 1995, pp. 487-505.

16. Mukhopadhyay, T., and Kekre, S. "Strategic and operational benefits of electronic integration in B2B procurement processes," Management Science (48:10), 2002, pp. 1301-1313.

17. Premkumar, G., Ramamurthy, K., and Saunders, C.S. "Information processing view of organizations: An exploratory examination of fit in the context of interorganizational relationships," Journal of Management Information Systems (22:1), 2005, pp. 257-294.

18. Son, J.-Y., Narasimhan, S., and Riggins, F.J. "Effects of relational factors and channel climate on EDI usage in the customer-supplier relationship," Journal of Management Information Systems (22:1), 2005, pp. 321-353.

19. Subramaniam, C., and Shaw, M.J. "A study of the value and impact of B2B e-commerce: The case of web-based procurement," International Journal of Electronic Commerce (6:4), 2002, pp. 19-40.

20. Yu, S., Mukhopadhyay, T., and Slaughter, S. "Organizational capabilities and the assimilation of electronic procurement in service industries," The 24th International Conference on Information Systems (ICIS2004), Seattle, WA, 2003, pp. 975-981.

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Resource-based View of the Inter-organizational Information System Capability:

A Field Study in Taiwan PC Industry