Time Lags Related to Past and Current IT Innovations in Japan: An Analysis of ERP, SCM, CRM, and Big Data Trends

Time Lags Related to Past and Current IT Innovations in Japan: An Analysis of ERP, SCM, CRM, and Big Data Trends

Hiroshi Sasaki (College of Business, Rikkyo University, Tokyo, Japan)
Copyright: © 2014 |Pages: 14
DOI: 10.4018/ijban.2014010103


The aim of this study was to examine two types of time lag related to IT innovations in Japan. The first is the time lag between newspaper articles and academic papers in the past. The second is the ongoing time lag with regard to the big data trend between the United States and Japan. This article explores a new analytical process based on two-dimensional maps proposed by Krinder et al. (2005) for visualizing and measuring time lags. After overviewing the big data trend in Japan, the author analyzed 2,910 newspaper articles and 550 academic papers published in Japan related to past innovations, as well as 734 newspaper articles from the United States and 173 from Japan related to the big data innovation. The results indicate that academic research for past trends lags business trends by 1-4 years. However, time lags in the big data trend could not be captured because of the difficulty predicting the point of inflection of S-shaped curves in an early stage of innovation. Accordingly, the author simulated future S-shaped curves to show the gap between the United States and Japan.
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Since the 1990s, IT innovations such as enterprise resource planning (ERP), supply chain management (SCM), and customer relationship management (CRM) have expanded throughout the world. A recently growing trend is big data. According to McAfee and Brynjolfsson (2012), “as the tools and philosophies of big data spread, they will change long-standing ideas about the value of experience, the nature of expertise and the practice of management. Smart leaders across industries will see using big data for what it is: a management revolution.” Articles related to big data appear in newspapers and business magazines almost every day. Implementation of new data analytics and acquisition of data scientists have become critical for managers. However, diffusion of technological innovation is not always the same in Japan as in the West, because of idiosyncratic business customs, culture, the competitive environment, and differences in IT infrastructure. In particular, as most big data-related technologies did not originate in Japan, firms need time to research overseas technologies. Consequently, a time lag develops.

In addition to geographical time lags, this paper focuses on another type of time lag: the one between current business trends and academic journal publication (Sasaki, 2010; 2014). The emergence of technological innovations motivates academic researchers to investigate new phenomena. However, time lags are inevitable, because empirical research often involves case studies on innovation, followed by more comprehensive studies using large-scale data. If the time lags become substantial, empirical studies have less chance of contributing to practitioners.

This paper is organized as follows. The next section surveys the big data trend to investigate the similarities and differences between current and past trends. After reviewing empirical tools for measuring time lag, we propose a new analytical process to examine the big data trend as well as to the ERP, SCM, and CRM trends that occurred in the 1990s and 2000s.

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