Exploiting RFID digital information in enterprise collaboration

Abstract

Purpose

The purpose of this paper is to investigate how a distributed network architecture, building on web‐service orchestration, data‐stream management systems and smart‐tagging technologies, can be employed to enable enterprise collaboration and decision making.

Design/methodology/approach

The methodology is based on a technology review in order to propose a network design as well as a field survey to identify and evaluate the relevance of radio frequency identification (RFID)‐enabled collaboration and decision‐support scenarios to industry executives.

Findings

The paper demonstrates the relevance of the proposed architecture and corresponding RFID‐enabled collaboration to business executives of the grocery retail sector. The responses show that some scenarios are more appealing to retailers than to suppliers and that certain processes should be done in collaboration.

Research limitations/implications

Research limitations and future research directions involve the evaluation of specific design alternatives, in the specific context as well as comparing the distributed architecture approach with a centralized architecture or with EDI which has traditionally been used to support enterprise collaboration.

Practical implications

The proposed architecture supports not only internal operations of network leaders, such as big retailers, but also suppliers who look into opportunities to benefit from the use of IT in enterprise relationships by gaining either process specificity or domain knowledge specificity.

Originality/value

The paper introduces a novel architecture that moves beyond the centralized web site paradigm to a distributed one. A European field survey is employed for the evaluation of several RFID‐enabled collaboration scenarios, providing insights to both researchers and practitioners (retailers and suppliers in the grocery retail sector).

Citation

Lekakos, G. (2007), "Exploiting RFID digital information in enterprise collaboration", Industrial Management & Data Systems, Vol. 107 No. 8, pp. 1110-1122. https://doi.org/10.1108/02635570710822778