The use of the analytical hierarchy process as a method of comparing innovation across regions: The examples of the equipment manufacturing industries of Shanghai and Xiamen, China

Abstract

Comparing innovation across regions is challenging. Innovation processes and outcomes are shaped by different actors, interactions, and institutions. Regional contingencies complicate the comparison as evident from the existing approaches to explaining innovation across regions. Quantitative innovation measurement approaches may quantify differences between regions, but disregard regional contingencies. Qualitative, heuristic approaches may understand an individual region’s innovation history and culture, but cannot quantify differences between regions. This paper introduces an adapted version of the analytical hierarchy process (AHP) to fill this methodological void. It shows that the AHP allows us both to consider regional contingency and to quantify differences between regions. This paper applies the AHP to compare innovation of the equipment manufacturing industries of Shanghai and Xiamen, China. It thus exemplifies how this method might be used for research and application in human geography, planning, regional science, and related fields.

Location Choice of Overseas High-Level Young Returned Talents in China

“…First, the system has a strong hierarchical order, with Beijing and its science organizations dominating the national system and functioning as a hub [45]. Second, the government and its involvement in arranging R&D is a highly correlated factor [46]; cities in the medium ranks of the system are changing their positions significantly, represented by the other municipalities and some provincial capital.…”

DAHP Expected Utility Based Evaluation Model for Management Performance on Interior Environmental Decoration – An Example in Taiwan

“…The research application covers diverse fields, e.g. Model for Measuring Korean Administrative Corruption (Yun, 2004), Approach to Convention Site Selection (Chen, 2006), New Product Development (Battistoni et al, 2013), and Comparing innovation across regions (Liefner and Jessberger, 2016). AHP at the modeling stage in this study continues the steps of Delphi process to calculate the relative weights of dimensions and factors.…”

The spatial configuration of innovation networks in China

“…Studies using concepts such as clusters, regional innovation system, innovative milieu and learning region employ a variety of terms to discuss the significance of the regional dissimilarity for innovation and the spatiality of regional inequality (Wei 2015). They suggest that innovative activities are the products of regions, and the regional economic and institutional environments affect the behavior of firms in the process of making and fulfilling innovation cooperation decisions (Sternberg and Arndt 2001;Blake and Hanson 2005;Howells and Bessant 2012;Liefner and Jessberger 2016).…”

“…Appearing as an extreme case of a triple helix innovation pattern proposed by Etzkowitz and Leydesdorff (2000), most scholars agree that the Chinese government (and the Communist Party) are powerfully involved in the process of innovation generation and continuously affect firms' approaches towards innovation, highlighting an important feature of the party-led and planning-oriented economy (Liefner and Jessberger 2016;. The general way is that the government sets up a series of formal laws/ regulations and informal societal norms/habits to shape and influence firm innovation behavior (Meyer et al 2012).…”

“…Meanwhile, in the case of China, the ongoing innovation process allows the coexistence of a specific variety of actors, such as public R&D institutes, universities, state-owned and private firms et al Little attention, however, has been paid to the great differences in China-specific context peculiarity (Hu and Lin 2013;Kafouros et al 2015). Firstly, the Chinese government is actively involved in innovation activities not only in finance and other types of support, but also as an important factor influencing the trend of the network configuration, for example with regard to the types of innovation activities carried out and partners chosen for innovation (Liefner and Zeng 2008;Hu and Lin 2013;Liefner and Jessberger 2016). Secondly, although some Chinese privately owned enterprises (POEs hereafter) have been successful in terms of innovation, state-owned enterprises (SOEs hereafter) normally dominate in certain industries and easily gain access to large-scale subsidies (Peighambari et al 2014;Du and Mickiewicz 2016).…”