Peter Vervest

Smart business networks: how the network wins

Realizing scenarios in which business is conducted through a rapidly formed network with anyone, anywhere, anytime regardless of different computer systems and business processes.

How should CIOs deal with Web-based auctions?

xploiting the Internet for commercial benefit has become a key theme for Chief Information Officers at most organizations. Significant advantages are to be gained for both sellers and buyers. Savings are made by reducing transaction costs, increasing the circle of potential customers as well as by improving the search-and-find capabilities for all parties concerned [1, 2, 4]. Web-based auctioning is a rapidly expanding application of the Internet. The matching of demand and supply at the best price at one specific point in time is the additional benefit of a Web-based auction. The advantages, however, must be considered against lower switching costs for auction participants. Are auctions always beneficial to the company? In particular, which technical and business arrangements must the CIO satisfy to give the organization a lasting advantage in this new field of electronic commerce? The following types of Web-based auctions can be distinguished as shown in Figure 1 and are further described here. Web-based Sales Auctions: One seller offering to as many buyers as allowed into the auction. Example: “Onsale” (www.onsale.com) offers 24-hour, interactive auctioning for all types of computer equipment and consumer electronics by means of an innovative arrangement called a “Yankee-auction.” Bids are sorted in order of price, then quantity, then bid time. When the auction closes, the highest bidder is considered the winner. Web-based Procurement Auctions: One buyer tendering his procurement needs via the Internet. Example: General Electric (www.tpn.geis.com) tenders its procurement needs to a selected set of suppliers via the Internet and subsequently uses auction techniques before issuing orders. Many more large companies as well as government bodies are currently considering or implementing these types of Internet-procurement systems. This requires multicriteria auctioning systems that optimize on price as well as other criteria such as product quality, delivery time, and reliability. Web-based Many-to-Many Auctions: Many suppliers offering to many potential buyers. Example: The Arizona Stock Exchange (www.azx.com) offers a call auction for stocks. In a call auction, trading takes place only at certain prearranged times—the “calls.” Between calls, orders accumulate. At the call, a price is established by identifying the supply and demand. Bringing sellers and buyers together at the same time, and at a single price, avoids the market spreads and random turbulence common in continuous markets. Current understanding of Web-based auctions is still limited. There is a significant theoretical base for traditional auctions [5], but the pervasive impact of advanced electronic communications is usually not addressed. Recent research suggests that almost any good or service can be put forward for electronic auctioning to the advantage of the business concerned, but this is not without risk [3]. However, the implications for the information and communications sys-

Embedded coordination in a business network

Information and communication technology enables a firm to maintain more links with more companies at much lower costs than before. This combined with the increasingly standardization of business processes and the application of modularity at the process level leads to embedded coordination. This case study describes how three unconnected business networks were integrated using modularity at the business process, or activity component, level and the role standardization played to implement embedded coordination. The case study was conducted at ABZ, a trusted Business Service Provisioner in the Dutch insurance industry. This study suggests that embedded coordination leads to improved performance of the business network under the condition that standardization is enforced.

The emergence of smart business networks

This article introduces the novel concept of smart business networks. The authors see the future as a developing web of people and organizations, bound together in a dynamic and unpredictable way, creating smart outcomes from quickly (re-) configuring links between actors. The question is: What should be done to make the outcomes of such a network ‘smart’, that is, just a little better than that of your competitor? More agile, with less pain, with more return to all the members of the network, now and over time? The technical answer is to create a ‘business operating system’ that should run business processes on different organizational platforms. Business processes would become portable: The end-to-end management of processes running across many different organizations in many different forms would become possible. This article presents an energizing discussion of smart business networks and the research challenges ahead.

Smart business networks: Concepts and empirical evidence

Organizations are moving, or must move, from todays relatively stable and slow-moving business networks to an open digital platform where business is conducted across a rapidly-formed network with anyone, anywhere, anytime despite different business processes and computer systems. Table 1 provides an overview of the characteristics of the traditional and new business network approaches [2]. The disadvantages and associated costs of the more traditional approaches are caused by the inability to provide relative complex, bundled, and fast delivered products and services. The potential of the new business network approach is to create these types of products and services with the help of combining business network insights with telecommunication capabilities.

Network horizon: An information-based view on the dynamics of bridging positions

We propose an information-based view of the dynamics of network positions and use it to explain why bridging positions become stronger. We depart from previous network dynamics studies that implicitly assume that firms have homogenous information about the network structure. Using network experiments with both students and managers, we vary a firms network horizon (i.e., how much information a firm has about the network structure) and the network horizon heterogeneity (i.e., how this information is distributed among the firms within the network). Our results indicate that firms with a higher network horizon occupy a stronger bridging position, especially under conditions of high network horizon heterogeneity. At a more general level, these results provide an indirect validation of what so far has been an untested assumption in interfirm network research, namely that firms are aware of their position in the overall network and consciously attempt to improve their position.

Passenger travel behavior model in railway network simulation

Transportation planners and public transport operators alike have become increasingly aware of the need to diffuse the concentration of the peak period travel. Differentiated pricing is one possible method to even out the demand and reduce peak load requirement. An evaluation of the potential effectiveness of strategies directed to flatten the demand distribution requires an understanding of the underlying factors that drive travel behavior (e.g., time-shifting, route change, mode change) with regard to price and service. In this paper, we present a passenger railway network simulation model with the intention of linking supply and demand. The objective is to evaluate the differentiated pricing impact on the passenger travel behavior, and consequently on the overall network performance, both financially and operationally. This paper focuses on the design and modeling approach of the travel behavior model

Introduction to Smart Business Networks

Correspondence: P Vervest, Professor of Business Telecommunications, E-mail: pvervest@fbk.eur.nl E van Heck, Professor of Electronic Markets, E-mail: evanheck@fbk.eur.nl L Pau, Professor of Mobile Business, E-mail: lpau@fbk.eur.nl Rotterdam School of Management, Erasmus University Rotterdam, PO Box 1738, 300 DR Rotterdam, The Netherlands. Journal of Information Technology (2004) 19, 225–227. doi:10.1057/palgrave.jit.2000031

The Network Factor — How to Remain Competitive

Abstract The network rather than the individual firm is becoming the focal point of economic development and business success. What should executives and managers do particularly well, or different, to thrive in the networked world? Based on the Discovery Event “The Networked Experience”, Beijing 18–23 May 2008, hosted by Tsinghua University (see www.sbniweb.org), we develop a number of propositions, or guidelines to understanding the network factor in todays competitive business arena. Building on the work of the Smart Business Network Initiative established in 2004 (Vervest, van Heck, Preiss, & Pau, 2005) we call for action to develop a unified theory of business networks.

Network transparency and the performance of dynamic business networks

Business networks have proliferated over the past three decades as many firms enabled by ICT have embraced the digital ecosystem form of organization. This implies that in addition to thinking of performance at the level of the individual firm, it becomes necessary to think in terms of performance at the level of the ecosystem, i.e. the business network as a whole, yet is not clear how to best conceptualize and measure business network performance. In this article, we show that business network performance can be conceptualized in three complementary perspectives: the firm perspective, the complex systems perspective and the customer perspective. We employ the customer perspective and develop two specific business network performance metrics, namely network effectiveness and network efficiency. Based on the information integration and visibility benefits that interorganizational systems (IOS) provide, we then develop a construct called network transparency. Using a series of network experiments with students, we find that an increase in network transparency increases business network performance in terms of network effectiveness and network efficiency. We thus show that the value of network transparency is measurable through clear metrics at the level of the business network as a whole.