Mobile content and service delivery platforms: a technology classification model

Abstract

Purpose

This paper seeks to propose a technology classification model for mobile content and service delivery platforms (MCSDPs), the core of mobile middleware technology providers' (MMTPs) value proposition.

Design/methodology/approach

The proposed model is grounded on existing literature and empirical research consisting of 40 in‐depth case studies with MMTPs and 102 semi‐structured interviews with top management from firms operating in the mobile content environment that already own or are interested in purchasing a MCSDP. Theoretical sampling was employed. The quality function deployment (QFD) technique was used to create the final technology classification schema.

Findings

The MCSDP technology classification model has three components: a MCSDP functional architecture, which describes platform structure in terms of its endowment of functionalities and capabilities; a MCSD classification schema, which allows the identification of a set of platform categories classified according to the range of functionalities usually possessed; and a technology classification schema consisting of a set of technology dimensions that directly influence platform efficiency and effectiveness.

Practical implications

The proposed model can be used for mapping existing and future MCSDP offer in terms of technological strengths and weaknesses and thus support decision‐making by platform vendors and buyers.

Originality/value

The main contribution is the creation of a reference framework capable of rigorously modelling the emergent phenomenon related to the rise of middleware platform providers within the mobile content environment. The paper also contributes to extending the existing QFD literature, since it demonstrates the house of quality tool's usefulness in a new context of application.

Citation

Ghezzi, A., Nogueira Cortimiglia, M. and Balocco, R. (2012), "Mobile content and service delivery platforms: a technology classification model", info, Vol. 14 No. 2, pp. 72-88. https://doi.org/10.1108/14636691211204879