一个理解移动商务未来的预见框架

Q2 Computer Science

Journal of Systems and Information Technology Pub Date : 2002-12-01 DOI:10.1108/13287260280000769

Shengnan Han, Ville Harkke, P. Ruggero, Ruggero Rossi De Mio

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引用次数: 3

摘要

在过去的几年里，3G移动商务世界的出现一直处于观望模式。现有的障碍对移动商务行业(MCI)的所有参与者都构成了挑战。向未来学习并发现通往理想未来的道路是移动商务业务成功的关键。在本文中，我们认为，为了发现通往未来市场的成功途径，MCI中的所有参与者都使用行业预见方法是非常重要的。我们提出了一个框架，用于创建行业预见和理解移动商务的未来。我们关注的是整个移动商务行业，并引入了两个广泛的变量;(1)移动商务产品和服务的采用和推广;(2)宏观经济发展趋势。基于这些变量，我们构建了四种预测情景:快速上升、快速下降、缓慢下降和缓慢上升。在这四种不同场景的基础上，我们提出了一些有前途的移动商务产品和服务的特点。我们正在使用信息收集代理，以便为我们的分析收集信息。预见框架将帮助所有参与者了解移动商务的未来。

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A foresight framework for understanding the future of mobile commerce

The advent of the 3G world of mobile commerce has suffered from the wait‐and‐see mode over the last years. Existing barriers pose a challenge to all actors in the mobile commerce industry (MCI). Learning from the future and discovering a route to a desired future are keys to successful mobile commerce business. In this paper we argue that it is very important that all actors in the MCI use an industry foresight approach in order to discover a successful route to future markets. We present a framework for creating industry foresights and for understanding the future of mobile commerce. We focus on the mobile commerce industry as a whole and introduce two broad variables; (1) adoption and diffusion of mobile commerce products and services; and (2) the macro‐economic development trend. Based on these variables we build four foresight scenarios: Rapid‐Up, Rapid‐Down, Slow‐Down and Slow‐Up. On the basis of these four different scenarios we suggest some features of promising mobile commerce products and services. We are using information‐gathering agents in order to collect information for our analysis. The foresight framework will help all actors understand the future for m‐commerce.

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来源期刊

Journal of Systems and Information Technology Computer Science-Computer Science (all)

CiteScore

4.40

自引率

0.00%

发文量

期刊介绍： The Journal provides an avenue for scholarly work that researches systems thinking applications, information systems, electronic business, data analytics, information sciences, information management, business intelligence, and complex adaptive systems in the application domains of the business environment, health, the built environment, cultural settings, and the natural environment. Papers examine the wider implications of the systems or technology being researched. This means papers consider aspects such as social and organisational relevance, business value, cognitive implications, social implications, impact on individuals or community perspectives, and the development of solutions, rather than focusing solely on the technology. The Journal of Systems and Information Technology is open to a wide range of research methodologies and paper styles including case studies, surveys, experiments, review papers, design science, design thinking and both theoretical and methodological papers. The focus of the journal will be to publish work that fits into the following broad areas of research: Behavioural Information Systems and Human-Computer Interaction, Data Analytics, Data, Information and Security, E-Business, Intelligent Systems and Applications, Logistics and Supply Chain Management/Optimisation, Social Media Analysis, Technology Enhanced Learning.