Abstract

This research presents the results of an exploratory study of how organisations operating in the Internet of Things (IoT) industry are building and innovating their business model (BM). Using an explorative sequential approach through the multiple-case study method, we apply the “Canvas BM” framework to explore the BM of three companies operating in IoT industry, namely Intel, Solair, and Apio. The paper finds the most important building blocks - key activities, key resources, and value proposition - and most critical related factors enabling IoT-oriented organisations to create and capture value. Furthermore, our results also suggest that the main difference in the processes of BM building and innovation depend on the different capabilities and competencies possessed by organisations. This study therefore advances the theoretical understanding of the critical factors for the value creation process in the IoT industry's organisations and offers interesting implications for management theory and practice.

1. Introduction

Over the last two decades, the Internet of Things (henceforth: IoT) has been in a constant state of evolution. Some of the most prestigious management-consulting firms, such as Gartner, McKinsey analysis, and ABI Research, forecast that IoT devices would grow from about 5 billion in 2014 to as many as 20 billion devices by 2020. In terms of hardware spending, consumer applications will amount to $1534 billion by 2020, while the use of connected things in the enterprise will rise to $1477 billion in 2020 (Gartner, 2015). Therefore, IoT is included by the US National Intelligence Council in the list of six “Disruptive Civil Technologies” with potential impacts on US national power (NIC, 2008).

4.2. Limitations and opportunities for future research

This study has a number of limitations that should be addressed. Firstly, the research was based on a case study method to explore IoToriented BMs. Although the case study research method is considered particularly useful for explorative analysis in managerial literature, it can make no claim to being typical because the sample was small and idiosyncratic. Thus, the findings are not generalizable in the conventional sense to the IoT industry and to other industries, because it is difficult to establish the probability that the data findings are representative of a larger population. However, this is a common limitation of the qualitative studies based on such research technique, rather than a specific weakness of this paper. Moreover, the use of questionnaire for data collection enabled us to reduce the predominantly non-numerical outcome of data that is usual in qualitative research.