![Sample our Environment & Sustainability journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5935/TOC-Subject-Sample-2021-Environment-Sustainability.jpg"})
Abstract
There has been unrest in the research community investigating the inoperability of an economic system under disaster situations. The inoperability input–output model (IIM), which is very popular in the risk management field, has become a center of argument, particularly from the input–output researchers, that IIM is a straightforward application of the standard Leontief input–output model. This paper revisits the concept of inoperability, rather than IIM, and proposes its new role in disaster impact analysis using a conventional tool, i.e. the RAS method, for illustrating how the inoperability of an economic system in the aftermath of disaster can be evaluated. The proposed framework is employed to examine the inoperability of industries resulting from the 1995 Kobe earthquake. The findings of the analysis reveal the usefulness of inoperability concept that can even incorporate resilience (gained operability) using the proposed framework of this paper.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Greenberg et al. (Citation2012) claimed that the IIM is one of the 10 most important accomplishments of the last 30 years in the risk analysis field.
2 This paper discusses only the static version of IIM, not the dynamic version of IIM (DIIM).
3 Oosterhaven (Citation2017) also mentioned the longer-term (negative) impact of financing the reconstruction activities. While this issue is important and needs more attention, the framework of the analysis in this paper focuses rather on the short-term impact of a disaster. Hence, the longer-term impact is not dealt with here.
4 While criticizing the core structure of IIM, Dietzenbacher and Miller (Citation2015) stated that the extensions of IIM with other analytical tools, for example, with event tree analysis in Santos et al. (Citation2014), are useful and interesting.
5 The details of the generalized hypothetical extraction method can be found in Dietzenbacher and Lahr (Citation2013).
6 An excellent summary for several variants of the RAS method can be found in Avelino (Citation2017).
7 Dietzenbacher and Miller (Citation2009) have proved that updating either a transaction matrix or the input-coefficient matrix using the RAS technique does not make any difference.
8 The details of this estimation procedure can be found in Miller and Blair (Citation2009).
9 Leontief (Citation1941) observed the changes in input-coefficient matrix, suggesting “proportional changes in the productivities of all the inputs of every separate industry or a proportional variation of the productivity of each separate commodity in all its various uses, or in some combination of these two simple types of technical change” (p. 107). Bacharach (Citation1970) interpreted this remark as “changing input-output coefficients obey a relationship of the form (1)” (p. 22). This made Leontief (Citation1941) the first one to propose a connection of this type.
10 This can be thought of as if the industry changed the location of intermediate inputs purchase (increased from outside of the region), due to transportation network disruptions in the damaged region by the disaster.
11 This can be considered that the industry increased the purchase of intermediate input within the damaged region due to damages of inter-regional transportation network.
12 Dietzenbacher and Lahr (Citation2013) note that the GHE can be applied also to the case of input coefficients increase resulting from the substitution of products in the production process of an industry.
13 The earthquake occurred in the early morning of 17 January 1995. Therefore, the 1995 data should capture the effects from the direct damages and the early stage of recovery and reconstruction activities.
14 These include the cities of Kobe, Amagasaki, Akashi, Nishinomiya, Sumoto, Ashiya, Itami, Takarazuka, Miki, and Kawanishi, and the towns of Tsuna, Awaji, Tsuna-gun Ichinomiya, Goshiki, Higashiura, Midori, Seidan, Mihara, and Nandan.
15 The sector classification of the Ashiya-Jinushi tables is also converted to 33 sectors from the original 34 sectors, as seen in Appendix.
17 Bacharach (Citation1970) and van der Linden (Citation1999) pointed out that a solution of the RAS technique is parametrically determined. In order to avoid any bias from the procedure, the results here are the average between column-first and row-first results.
18 Mining industry (4) also has a large decrease in the regional purchase coefficient. Because their production levels and regional purchase coefficients in both 1990 and 1995 are relatively small, they are not included in the discussion here.
19 Non-ferrous metal (12) has an excessively large value (8.0870) for r in Table . This results from their r value (1.1293) and d value (7.2957) in Table . If d is completely internalized with r in Equation 7, it would become 8.2390. Since the value of r in Table is smaller than this, a small portion of d is also internalized in s.
20 Because of the complexity of production system and various production processes among industries, these results should be further and carefully investigated.
21 The impact from decreased earnings cannot be handled in this framework. In order to include it, one may want to employ a Miyazawa enlarged input–output table.