Silviase/jgov_v1.4_full_ann huggingface dataset:
[英文概要]

Study on Effective Recycling Process of Titanium Alloy Machined Chips by Using Hydrogen

Principal Investigator: Katsuyoshi KONDOH

Institution: Joining and Welding Research Institute, Osaka University

11-1 Mihogaoka, Ibaraki-City, Osaka 567-0047, JAPAN

Tel & Fax: +81-6-6879-4369

E-mail: kondoh@jwri.osaka-u.ac.jp

## [Abstract]

Key Words: Solid-state recycling process, Titanium machined chips, Hydrogen, Powder, Sintering, Mechanical properties

Titanium and its alloys are widely used in industrial fields because of their high specific strength, excellent corrosion resistance and biocompatibility. In particular, from a fuel efficiency improvement and $ CO_{2} $ gas reduction points of view, titanium alloys are recently employed in aircraft components, combined with carbon fiber reinforced plastics. A high dimensional tolerance is strongly required in the components as well as high quality. Then the machined finish is necessary in the component production. When raw titanium (Ti) billets are machined, many metal ends occur and are recycled via the conventional re-melting process in vacuum. Only 30% of the wastes are possibly reused as raw materials in the process.

In this project, an advanced solid-state recycling process of machined Ti wastes was established to completely reuse them in recycled Ti materials fabrication via powder metallurgy technique. In particular, large chips with spiral structures were completely refined to fine Ti powders with hundreds $ \mu $ m diameter via grinding process after hydrogenation reaction of Ti chips. This is because titanium hydride ( $ TiH_{2} $ ) are brittle and easily crushed by ball-milling process to fine powders. The optimization of process parameters in the hydrogenation reaction, powder compaction, sintering with dehydrogenation, and extrusion were conducted to fabricate the recycled Ti-64 alloys. They indicated the same mechanical properties such as tensile strength, elongation, and fatigue stress as those of commercial virgin fiber Ti-64 alloys. In analysis on cold compaction behavior of $ TiH_{2} $ brittle powders, a modified Cooper-Eaton model was applied to quantitatively evaluate their densification mechanism. According calculation results, a high density $ TiH_{2} $ powder compact, which had a relative density of about 85% and no surface crack, was obtained by cold pressing.

Regarding a scale-up ability of recycled Ti alloys, from a view point of the statistical evaluation of their mechanical properties, tensile test on the recycled Ti specimens of 750 pieces was carried out. It was clarified they had a high reliability of tensile strength through quantitative analysis on their standard deviation.
In addition, a novel materials design for high strength and ductility Ti materials by a small addition of hydrogen was established. In general, hydrogen addition into metals causes a drastic decrease of their mechanical properties. In this group, however, less than 0.2~3 mass% hydrogen addition into $ \alpha $ -Ti effectively formed <0001> fibre-texture casuing significant increment of Young's modulus and yield strength, and also uniformly dispersed $ TiH_{x} $ compounds preventing deformation twins propagation, resulting in a high elongation in tensile.
2305 外国為替資金特別会計

平 成 3 0 年 度 歲 入 概 算 見 積 書

1. 平成 30 年度歳入概算見積額総表 …… 1
2. 平成 30 年度歳入概算見積額明細表 …… 2
(会計)05 外国為替資金 …… 2
平 成 3 0 年 度 歲 入 概 算 見 積 額 目 次
2305 外国為替資金特別会計
区	分	ページ	区	分	ページ
平成 3 0 年度歳入概算見積額総表	1
平成 3 0 年度歳入概算見積額明細表	2
(会計) 05 外国為替資金	2
(款) 01 外国為替等売買差益	2
(項) 01 外国為替等売買差益	2
(款) 02 運用収入	2
(項) 01 運用収入	2
(款) 03 雑収入	3
(項) 01 雑収入	3
平 成 3 0 年 度 歲 入 概 算 見 積 額 総 表
2305外國為替資金特別会计
区 分	当 初 見 積 額	3 0 年 度 概 算 見 積 額	对 前 年 度 較 减 (B-A)	明細書 真 数
計(A)	計(B)
05 外 国 為 替 資 金	2,528,274,654	2,802,306,409	274,031,755	2
01 外 国 為 替 等 壳 買 差 益	150,000,000	155,662,500	5,662,500	2
01 外 国 為 替 等 壳 買 差 益	150,000,000	155,662,500	5,662,500	2
02 運 用 収 入	2,378,274,394	2,646,643,649	268,369,255	2
01 運 用 収 入	2,378,274,394	2,646,643,649	268,369,255	2
03 雜 収 入	260	260	0	3
01 雜 収 入	260	260	0	3
会 計 計	2,528,274,654	2,802,306,409	274,031,755
平 成 3 0 年度 歳 入 概 算 要 求 額 明 细 表
2305外国為替資金特別会计
事項	当見積額	3 0 年度概算見積額	对前年度比較增△減	備考
274,031,755
05 外国為替資金	2,528,274,654	2,802,306,409
01 外国為替等売買差益
01 外国為替等売買差益	150,000,000	155,662,500	5,662,500	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予定額	120,000,000	130,000,000	130,000,000	150,000,000	150,000,000
決算額	891,695,113	902,143,825	134,037,328	172,061,016	208,449,339
02 運用収入
01 運用収入	2,378,274,394	2,646,643,649	268,369,255
2,377,338,773	2,643,612,961	266,274,188	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予定額	2,086,102,123	2,075,133,236	2,293,872,414	2,471,283,227	2,487,337,228
決算額	2,093,649,949	2,407,354,535	2,411,239,711	2,533,900,001	2,187,202,182
外貨資金等の運用による収入見込額を計上
1.外貨預付金利子	18,743,442(	51,288,920)
2.外貨証券運用益	2,528,626,071(	2,256,007,060)
(1)外貨証券受取利子	2,418,074,700(	2,184,663,939)
(2)外貨証券償還益	110,551,371(	71,343,121)
3.特別引出權利子	1,140,509(	324,874)
3 0 年 2 月 1 日から 3 1 年 1 月 3 1 日までの期間の特別引出權(S D R)純利子額の見込額(注)国際通貨基金(IMF)協定第2 0 条の規定により、S D Rについては、保有額に対して利子が、純累積配分額に対して手数料がそれぞれ発生することとなるが、両者はIMFの事務処理上、相殺の上決済されることとなっており、保有額が純累積配分額を上回るときは純利子額が支払われることになる。
4.円貨貸付金利子	4,697,410(	1,466,792)
5.外貨貸付金利子	90,292,992(	68,166,881)
6.特別引出權証券利子	72,810(	11,990)
7.財政融資資金預託金利子	39,727(	72,256)
特別会計に関する法律第1 1 条及び第1 2 条の規定に基づく財政融資資金への預託金から生ずる利子収入見込額	2,643,612,961(	2,377,338,773)
02 国際通貨基金報酬	935,621	3,030,688	2,095,067	2 4 年度	2 5 年度	2 6 年度	2 7 年度	2 8 年度
予定額	878,679	44,516	36,897	3,682	11,145
決算額	275,446	37,909	29,238	6,585	510,467
IMFの保有する円が一定の水準を下回った場合に、その下回った部分に対しIMF協定第5条第9項の規定により、IMFから支払われる報酬額の見込額
3 為

事項	当初價	30年度概算見積額	對前年度比較增△減	備考
0
0
24年度	25年度	26年度	27年度	28年度
予定額	10	10	10	10	10
決算額	0	0	0	0	0
小切手支払未済金收入見达額を計上
0	24年度	25年度	26年度	27年度	28年度
予定額	100	100	100	100	100
決算額	5,495,310	17,709,295	1,441,414	29,094,385	235,074,012
收入見达額を計上
0	24年度	25年度	26年度	27年度	28年度
予定額	7,000	1,050,000	1,050,000	1,050,000	675,000
決算額	210,382	96,496	12,893	124	0
指定預金利子收入見达額を計上
国等における温室効果ガス等の排出の削減に配慮した契約の推進に関する法律(環境配慮契約法)第8条第1項の規定に基づき、平成27年度における復興庁の温室効果ガス等の排出の削減に配慮した契約(環境配慮契約)の締結実績を次のとおり公表します。

### 1. 平成27年度の経緯

環境配慮契約法及び平成19年12月に閣議決定された「国及び独立行政法人等における温室効果ガス等の排出の削減に配慮した契約の推進に関する基本方針」に基づき、可能なものから温室効果ガス等の排出の削減に配慮した契約（以下「環境配慮契約」という。）の推進を図ることとした。

### 2. 平成27年度における復興庁の環境配慮契約の締結状況

基本方針において具体的な契約方法が定められている、①電気の供給を受ける契約(裾切り方式)、②自動車の購入及び賃貸借に係る契約(総合評価方式)、③船舶の調達に係る契約(船舶の設計(プロポーザル方式))、④省エネルギー改修事業(ESCO事業)に係る契約、⑤建築物に関する契約(プロポーザル方式)、⑥産業廃棄物の処理に係る契約(裾切り方式)のうち、⑥に関連して以下のとおりとした。

## ○産業廃棄物の処理に係る契約

復興庁においては入居している民間ビルの指定業者との契約であり、競争できないため環境配慮契約方式による契約を行っていない。
# CPRC Discussion Paper Series

# Competition Policy Research Center Fair Trade Commission of Japan

Network Effects in the Japanese Word-Processing Software Market

Yoshihito YASAKI

Research Center for Advanced Science and Technology,

University of Tokyo

Competition Policy Research Center,

Fair Trade Commission of Japan

Reiko MURAKAMI

Competition Policy Research Center,

Fair Trade Commission of Japan

CPDP-2-E December 2003

1-1-1, Kasumigaseki, Chiyoda-ku, TOKYO 100-8987 JAPAN

Phone:+81-3581-1848 Fax:+81-3-3581-1945

URL:www.jftc.go.jp/cprc.html

E-mail:cprcsec@jftc.go.jp
# Network Effects in the Japanese Word-Processing Software Market $ ^{*} $

Research Center for Advanced Science and Technology, University of Tokyo

4-6-1, Komaba, Meguro-Ku, Tokyo 153-8904 Japan

yasaki@aee.u-tokyo.ac.jp

Visiting Researcher

Competition Policy Research Center, Fair Trade Commission of Japan

1-1-1 Kasumigaseki, Chiyoda-Ku Tokyo 100-8987 Japan

yoshihito_yasaki@jftc.go.jp

Reiko MURAKAMI

Competition Policy Research Center, Fair Trade Commission of Japan

1-1-1 Kasumigaseki, Chiyoda-Ku Tokyo 100-8987 Japan

reiko_murakami@jftc.go.jp

December 2003
## Abstract

This paper examines the importance of network effects in the Japanese market for word-processing software in the period between 1998 and 2001, using hedonic price and nested logit models. This was a period in which Microsoft Word had a large and steadily increasing share of the market. The presence of network effects was verified in the full regressions covering the entire period. Separate regressions for two consecutive years showed that network effects, as measured by the positive effect of the size of the user base on the product price or on the probability of the software group being chosen, were weak or insignificant in the beginning of the sample period. The paper discusses data and methodological issues, and possible reasons for these results, including the effects of switching costs.

Keywords: Network Effects, Software, Hedonics, Discrete Choice Model, Switching Costs.

JEL Classification Numbers: L86; L11; L13.
### 1. Introduction

The past decade has seen a rapid diffusion of word-processing software in Japan. As of March 2003, 63.3% of all ordinary households in Japan had at least one PC (Consumer Confidence Survey, Economic and Social Research Institute, Cabinet Office), and as of May 2000, 87.7% of all home PC users used word-processing software (Nikkei Newspaper). Justsystem's Ichitaro dominated the Japanese market for word-processing software until the mid-1990s, but Microsoft's Word overturned it around 1996-1997, and Word's market share has been increasing slowly but steadily since then.

A firm may be able to keep a high market share because its product displays a high cost-performance. It could also do so when there are network effects or switching costs. $ ^{1} $

This paper examines whether network effects were at work in the Japanese market for word-processing software in the period between 1998 and 2001, and, if so, to what extent. It also discusses whether firms with small market shares can still attract consumers by providing superior products.

Empirical research measuring network effects in individual markets has been on the increase since the 1990s. Common methods for measuring network effects include hedonic pricing models, discrete choice models and vector auto-regressive (VAR) models.

Hedonic pricing models estimate how product prices are dependent on product characteristics. When there are incompatibilities between products
where compatibility is in fact desired and if products with high market shares display high prices, controlling for product characteristics we may interpret this as evidence of network effects. Examples of this line of research include Brynjolfsson and Kemerer (1996) and Gandal (1994) who studied the US spreadsheet software market, Ohashi (2003a) who studied the US VCR market, and Asai and Tanaka (2003) who studied the Japanese PC market. Tanaka, Yasaki and Murakami (2003) discussed competition policy when both network effects and innovation are present and performed a hedonic analysis of the Japanese markets for spreadsheets and routers as well as word-processing software.

There is a growing literature measuring network effects in individual markets by directly modelling consumers' discrete choices. Nested logit (NL) is the common specification in these models. In NL models, consumers' choice alternatives are grouped together according to the correlation between utilities they would get from each choice. Consumers make two decisions, one regarding the choice of a group and the other regarding a particular alternative within this group. If consumers are more likely to choose products belonging to groups with high market shares, controlling for product prices and characteristics, we interpret that network effects are at work. NL models incorporate elements of hedonic pricing models in that product characteristics are included as control variables. Park (2003) and Ohashi (2003b) separately analysed the US VCR market using NL techniques. Rysman (2003) analysed indirect network externalities that arise between the number of advertisements and the number of consumers in the US market for Yellow Pages.

VAR models are used to test whether there is intertemporal correlation
between two or more time series to investigate the presence or otherwise of positive feedback between them. Tanaka (2002) analysed network effects in the Japanese mobile phone market using both hedonic and VAR techniques, while Tanaka (2003) investigated the Japanese game software industry using VAR models.

This paper employs both hedonic pricing and NL models to test for the presence of network effects in the Japanese word-processing software market. As far as we are aware, this is the first attempt to measure network effects in word-processing software in any geographical market.

The rest of the paper is organised as follows. Section 2 briefly reviews the state of the word-processing software market in Japan, and section 3 explains how network effects may arise in that market. In section 4 we discuss the data we used and begin our empirical analysis of the Japanese word-processing software market between 1998 and 2000 or 2001. Section 5 explains the hedonic pricing technique and the results we obtained from them. Network effects seem to have been present when data from the three-year period between 1998 and 2000 are used, but when data from two consecutive years are grouped together and each group is estimated separately, network effects were found not to have been significant in the beginning. Similar results are obtained when lagged value of the network effect variable are used. Section 6 explains the NL technique and the results we obtained from them. Similar intertemporal patterns regarding observed network effects are obtained. Section 7 discusses various issues including data and methodological limitations, and the possibility that the presence of switching costs gave rise to such intertemporal patterns. Section 8 discusses how Microsoft was able to gain a dominant market position in the latter half of the
1990s. Using results from a questionnaire survey of users, we discuss in section 9 the possibility that technological progress slowed down since Microsoft secured a high and stable market share. Section 10 concludes our paper.

### 2. Overview of the Market

Word-processing software diffused rapidly among Japanese households as PCs themselves did in the 1990s. Figure 1 shows the volume and value of shipment of word-processing software in the Japanese market in flow terms since the late 1980s. Both volume and value of shipments increased rapidly throughout the 1990s. It should be noted that the word-processing component in Office-type integrated business software is included in the data. In such cases, the value is divided equally between its major components such as word-processing, spreadsheet and database.

Figure 2 shows how the domestic market shares of major word-processing software products by producers evolved between 1994 and 2000. Ichitaro had a market share of over 50% in the first half of the 1990s, but was overturned by Word in the latter half. In the late 1990s Word kept a high, stable and slowly increasing market share. $ ^{2} $

Figure 3 shows how the list prices (or catalogue prices) of the most
recent versions of each major software product changed since 1991. $ ^{3} $ The price of both Ichitaro and Word stayed constant at 58,000 yen until 1995, but the situation changed drastically in 1996 when the list price of Ichitaro was lowered to 40,000 yen and that of Word to 15,000 yen. Prices were further reduced in 1997, Ichitaro to 20,000 yen and Word to 11,180 yen, and these prices remained the following year. A rapid market share reversal took place parallel to this. In 1999 the price of Word was raised to 18,800 yen. Strategic penetration pricing is often employed in industries with network effects or switching costs, and such pricing policies may have been used in this market from 1996 on. $ ^{4} $

The fact that Microsoft was able to increase its market share in the late 1990s may have been because Word was less expensive than Ichitaro, controlling for product characteristics. It may also have been because Microsoft benefited more from network effects than did Justsystem because Microsoft had already acquired a larger market share. In the next section we briefly show why network effects are likely to be at work in the market for word-processing software. Subsequent sections discuss empirically whether network effects really were present in this market in the period between 1998 and 2000 or 2001.

### 3. Network Effects in Word-Processing Software Market

Network effects are said to be at work if the benefit accruing to each individual consumer from using a particular good or service is dependent on
the number of other consumers who use compatible goods or services. There are two reasons why we think network effects may be present in the market for word-processing software.

First, documents written using word-processing software will generally be used by the writer herself, but generally also will be given to others to read and/or print out via diskettes, CD-ROMs, LANs and the Internet. The benefit to the writer will be greater the larger the number of other people who use software compatible with her own. Thus, direct network effects through exchange of files tend to be at work. $ ^{5} $

Second, in complement to the above, when a consumer starts to use a software product she will benefit from help given by others around her who use similar software. Moreover, the more consumers use a particular software product the larger will be the demand for guidance on how to use it or how to do particular tasks using it, and the more manuals and magazine articles will likely be written. The presence of such texts will benefit consumers further. Thus, indirect network effects also may be at work.

### 4. Data Set

### 4.1 Data Source

GFK, a market research firm, compiles average retail price and volume figures for various IT products from point-of-sale (POS) data from approximately 3,000 selected retailers. Our data set comprises average retail price and volume for all word-processing software products sold at those
retailers in the months of December 1998, December 1999, December 2000 and December 2001. We thus have monthly data from those four points in time, a year apart from each other. Henceforth, we use terminology whereby Word, Ichitaro, and other such software each comprises a software group, and different versions of software, products that run on different operating systems, and products sold under different discount programmes (e.g. student discounts and academic discounts) are treated as different software products.

Usage share data for each software group for each period come from the IT Basic Survey by Nikkei Market Access that we mentioned in section 2, and are based on replies (multiple) to a questionnaire survey of home PC users. Data on the number of ordinary households (Population Census: 1st October 1995, 1st October 2000), population estimates (Statistics Bureau, Ministry of Public Management, Home Affairs, Posts and Telecommunications, 1st October each year), PC penetration rate in ordinary households (Consumer Confidence Survey, Economic and Social Research Institute, Cabinet Office, end of March each year), and word-processing software usage rate among home PC users (Nikkei Newspapers: May 1998, May 1999, June 2000; Nomura Research Institute: March 1997, March 1999) are used in calculating the number of users for each software group.

### 4.2 Sample Selection

We restricted ourselves to stand-alone products, so integrated business software is not included. The sale of products falling under software groups other than Word and Ichitaro was extremely low throughout the period, so data for these are excluded. English-language versions, products for primary school students (e.g. Ichitaro Smile), Java-based products (e.g. Ichitaro ARK),
and other products for which characteristics were hard to determine were also excluded.

During the course of these years, the majority of PC users used Windows PCs. Also, the sale of products given academic discounts was much lower than that of products not given such discounts. Macintosh versions of word-processing software would not normally be an alternative for Windows users, and non-academic users cannot get academic discounts legitimately. Thus, Macintosh versions and academic discount versions were also excluded from our data set.

The above streamlining gives us a sample size of 76, and the composition of the sample is shown in Table 1. It should be noted that data on the same software product is treated as a different data point if they come from different points in time.

### 4.3 Variables

#### 4.3.1 Product Characteristics

One of the hardest tasks we faced was that of identifying the variables that represent product characteristics. Word-processing software had acquired numerous functional abilities by the late 1990s, and counting them all up would lead to insufficient degrees of freedom in the analysis. Specifying all product characteristics and evaluating each product with respect to these characteristics would be extremely hard in any case for the following reasons. First, many characteristics cannot easily be reduced to a numeric scale or even to a dummy variable (e.g. cleverness of Kana-Kanji transformation function). Second, not all product characteristics are written out in a comparable form in catalogues or on websites. Third, by the late
1990s, PC magazines and trade journals had stopped carrying articles that compare different software products in depth.

Many products characteristics are common to all or most products, and these effectively go out of consideration when a consumer decides which product to purchase. For instance, by this period all products allowed pictures to be imported into document files at specified locations. These functions do not differentiate products. In our analysis we focused on those functions that were either emphasized by the producer in advertisements and manuals or featured heavily in magazine articles and guidebooks when the products went on sale. These functions are the ability to store multiple clippings ( $ D\_MULTIPLECLIPS $ ), the presence of a working window ( $ D\_WORKINGWINDOW $ ), and worksheets to which files made by other software can be imported and saved as one file in the same way a number of Excel sheets can be saved as one file ( $ D\_WORKSHEET $ ), as well as those additional functions that are not an integral part of the word-processing software but are nevertheless used normally in conjunction with the software. Such additional functions include Kana-Kanji transformation ( $ D\_JP $ ) and voice recognition (hardware and software) ( $ D\_VOICE $ ). $ ^{6} $ Considering that consumers take into account information obtained from advertisements, manuals and guidebooks, it seems natural to think that the availability or otherwise of these functions influence their decisions.

We have also included a variable representing Lite versions of software, which supposedly provide a faster response to typing by concentrating on basic functions and shedding as many additional features as
possible (D_LITE).

#### 4.3.2 Network Effects

Either usage market share (SHARE) or the number of users of each software group in each period may be taken to represent network effects. We have not been able to obtain information on the latter, so we calculated it in the following manner.

First, we assumed that the average number of people in each ordinary household changed linearly over time, and calculated this number for the 1st of April of each year from the numbers for 1995 and 2000 and the population statistics for each year. From these and the data on PC penetration rate, the number of households with PCs was calculated. We think in terms of the number of households, not persons, regarding software usage in what follows. $ ^{7} $

We then calculated the number of households that had word-processing software from the number of households with PCs and the word-processing software usage rate among PC users. The usage rate data for 1998, 1999, and 2000 are available from Nikkei, and those for 1997 and 1999 from Nomura Research Institute. The number of households with PCs was accordingly calculated in two incomplete time series, which were interconnected by multiplying a constant to the Nomura-based series so that the 1999 figures are equal. $ ^{8} $

The number of households that have products under each software