Social e-business as support for construction e-procurement: e-procurement network dynamics

doi:10.1016/j.autcon.2014.03.019

Automation in Construction

Volume 43, July 2014, Pages 180-186

https://doi.org/10.1016/j.autcon.2014.03.019 Get rights and content

Highlights

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E-procurement network growth is discussed regarding the social network paradigm.
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Game theory is used to model e-procurement and social network dynamics.
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Based on the models proposed, two theorems are formulated.
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Several computer simulations are developed to get in-depth results.
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The role of social e-business as a support to e-procurement is discussed;

Introduction

If correctly designed and implemented, construction e-procurement platforms may increase performance-based competition, stimulate suppliers' noncontractible investments, encourage trust development and promote project quality [9], [17]. Therefore, e-procurement networks, which are constituted by buyers and suppliers, will be able to grow and consolidate, which is beneficial to buyers and suppliers [1] but also to e-procurement service providers, who will be able to increase profits. However, it is pertinent to ask if the e-procurement networks generated will tend to grow indefinitely, as it seems to happen in the well-known social networks [24], and what management approaches service providers should implement in order to encourage growth and obtain maximum benefits. It is also pertinent to discuss if Social e-business [10], which is an e-business approach that integrates several social networking tools, having in mind that social networking approaches should focus on collaborative processes, win–win relationships and supply chain integration instead of competition-based situations, may potentiate this growth. As stated by Grilo [14] an atmosphere of co-operation between firms, where they may have mutual expectation of long-term commercial interaction, is very important to the emergence and sophistication of innovative systems. Furthermore, the frequency and volume of information and financial exchanges and social contacts also largely influence the adoption of e-procurement instruments, providing the adequate environment for a growing growth rate.

In this sense, two models to support deeper analysis of social and e-procurement network dynamics are proposed, which were developed using game theory [19]. Based on the models developed, two theorems were deduced and discussed and three computer simulations were developed to support in-depth network dynamics analysis. Afterwards, a new vision for e-procurement platforms is discussed considering the results of network dynamics analysis.

Section snippets

On the dynamics of e-procurement networks

The developments of e-procurement networks based on electronic platforms are generating a wide range of benefits to improve supply chains and, therefore, are gaining popularity and their respective benefits have been largely discussed [4], [12], [18], [22], [23], [27], [29]. Among the reasons for such debate is the fact that e-procurement systems emerge promoting a more integrated, efficient and performance-based vision of procurement [7], [8], [11], [20], [25], facing a wider range of

Methodology

In the present study, theoretical models for social and e-procurement networks will be proposed using the formulation developed by game theory. E-procurement network (PN) and social network (SN) are defined as sets of members exchanging services and open to deny and accept new members at each time, and so modeling their dynamics implies:

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modeling benefits and costs for its existing members;
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modeling the decision process of each member to stay or to leave the network;
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modeling the decision process

A theorem on the dynamics of social networks

According to Eq. (1) and providing that α ⋅ N_SN(t) − C is positive for t = t₁, then it can be concluded that:

Theorem 1

The growth rate per time unit of the number of members of a social network is positive and grows proportionally to N_SN(t) for t ≥ t₁ assuming that the expected number of new members per time unit, E(t), is proportional to the net benefit for each new member.

Proof

$E (t) = w \cdot [α \cdot N_{SN} (t) - C] or E (t) = α \cdot w \cdot N_{SN} (t) - w \cdot C .$

Confirming that E(t) grows proportionally to N_SN(t).

Obviously, if α ⋅ [N_SN(t)] > C for t = t₁, then no member will

Parameter estimation

An important virtue of the proposed models to study e-network is the very small number of parameters adopted to describe their dynamics: α and β_s or β_p as the benefit constants for a potential new member of a social network and of a supplier or a procurer, respectively, for a procurement network. The other key parameters C, C_p, C_s can be considered as decision variables used by the manager of the procurement network to control its dynamics.

Therefore, the following method to estimate α, β_s, or β_p

Discussion of results

The mathematical models developed allowed a deeper analysis of social and e-procurement network dynamics and supported the formulation of two theorems based on their behavior. The first theorem shows that social networks show the network effect providing that service provider keeps network with a constant entrance cost per member. The second theorem shows that e-procurement network dynamics is more complex; as it is shown, for a specific N_s(t) = N_s, (or N_p(t) = N_p), growth rate decays with N_p(t)

Conclusions

E-procurement networks are becoming crucial to improve supply chain potential; they increase information and bidding competition and they may support added value services on procurement and supply chain management. These networks are based on the decision of membership by procurers and suppliers based on their perception of costs and benefits which depend on the members' potential to buy or to sell as well as on how e-procurement network is managed namely in terms of services and fees.

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Social e-business as support for construction e-procurement: e-procurement network dynamics

Highlights

Introduction

Section snippets

On the dynamics of e-procurement networks

Methodology

A theorem on the dynamics of social networks

Parameter estimation

Discussion of results

Conclusions

First page preview

Electron. Commerce Res. Appl.

Automat. Constr.

Automat. Constr.

Technovation

Ind. Mark. Manag.

J. Purch. Supply Manag.

Reducing buyer search costs: implications for electronic marketplaces

Manag. Sci.

Information technology, incentives, and the optimal number of suppliers

J. Manag. Inf. Syst.

E-business and E-commerce Management

The impact of information technology on the organization of economic activity: the “move to the middle” hypothesis

J. Manag. Inf. Syst.

Regulating Contracts

Green Paper on Expanding the Use of E-procurement in the EU

Electronic procurement in supply chain management: an information economics-based analysis of electronic markets

J. Supply Chain Manag.