Silviase/jgov_v1.4_full_ann huggingface dataset:
# 生協の宅配事業等を通じた見守り支援（見守り協定第1号）

## 実施地域の概要（高知県）

## ■ 実施地域の概要（高知県）

人口の46％が高知市（337千人、65歳以上92千人、高齢化率28%、153千世帯）に集中しており、高知市以外の地域では高齢化はさらに深刻な状況。

平成２７年国勢調査によると、県内の一般世帯のうち、高齢者のいる世帯は４８パーセン

このうち、高齢者のみの独居（単身）世帯と高齢夫婦のみの世帯を合わせた割合は約62%を占め、年々増加するものと見込まれる。

## 【平成27年データ】

· 総人口

728千人

· 総世帯数

319千世帯

· 平均世带人数

・高齢者人口（高齢化率）

うち、1人のみ世帯

うち、夫婦のみ世帯

2.3人

237千人（32%）

52千世帯

· 組合員数

42千世帯

· 世帯加入率

96,558人（2017年2月末）

約30%

## 事業・組合員活動の実施状況

## ■事業の特徴

行政との協定にもとづき、県下全域を配送エリアとする宅配のインフラを活用し、見守りを実施。

生協と行政の間での地域見守り協定は、平成19年にこうち生協が全国で初めて締結した。以降、高知県内全域をカバーする宅配事業や夕食宅配時における配送員の見守り、店舗事業における職員等の見守りを実施している（見守り事例は、p.4参照）。

（参考）宅配事業について

・配送エリア：県下全域（配送拠点は県内6カ所）

· 配送車数 : 94台

・共同購入・個人宅配（週1回配送）の注文書発行人数：49千人

・夕食宅配（月～金曜配達）の1日当たり食数：920食前後
## 事業・組合員活動につながる組合の取組の特徴等

## （１）見守り協定の背景

・地域の中で支援が必要と思われる世帯や子どもの安全などの見守り活動には、主に地域住民の方々の相談や支援に取り組まれている民生委員・児童委員の皆様が中心的な役割を担っていたが、児童虐待や悪徳商法といった深刻な問題への対応も増加してきた。

そのため、高知県では、平成19年度に民生委員・児童委員制度創設90周年を迎えたことを契機に、日ごろから地域住民の方々と接する機会の多い民間事業者と連携した見守り活動のネットワークを構築することとした。

・協力する民間事業者と、高知県民生委員児童委員協議会連合会及び高知県の間での三者協定「高知県における地域の見守り活動に関する協定」を締結している。

## （2） 協定參加事業者

・地元新聞社、地元スーパーチェーンに続いて3番目に協定に参加。

く高知県庁での見守り協定調印の様子>

## 【現在の協定参加事業者】

○高知新聞販売所 高新会・株式会社高知新聞社（平成１９年４月６日）

○株式会社サンプラザ（平成19年8月28日）

○こうち生活協同組合（平成19年10月19日）

○高知ヤクルト販売株式会社（平成１９年１１月２９日）

○四国電力株式会社（高知支店・中村支店）（平成20年10月8日）

ＯＪＡグループ高知（県下の全農協）（平成２２年１月１５日）

○高知医療生活協同組合（平成22年11月25日）

○株式会社サニーマート（平成26年5月29日）

○株式会社セブン - イレブン・ジャパン（平成27年11月27日）
## 行政や他の組合、医療・福祉事業者等との連携、役割分担等の状況

## ■県との地域見守り協定等の概要

①地域見守り協定の目的（「地域見守り協定」第1条より）

協定は、誰もが住み慣れた地域で安心して暮らし続けることができることを目指して、地域の中で支援が必要と思われる世帯や子どもの安全などの見守り活動に対して、こうち生活協同組合、高知県民生委員児童委員協議会連合会及び高知県が積極的に協力し、地域福祉の向上に寄与することを目的とする。

## ②こうち生協の協力内容（「地域見守り協定」第2条より）

1 職員に対して協定の趣旨を周知し、日常の業務の範囲において協力可能な体制の整備を行う。

2 職員は、共同購入・個人宅配の利用者及び配送ルート上の住民に関して何らかの異変を察知した場合は、速やかに地域を管轄する民生委員等に連絡・通報する。

3 連絡・通報よって、民生委員・児童委員の支援活動を実施するにあたり生じる諸問題に対して、生協は一切の責任を負わない。

4 連絡・通報に係る経費はこうち生活協同組合の負担とする。

## ③こうち生協が具体的に取り組むこと

・配送ルート上で何らかの異変を察知した場合は、各市町村の民生委員等に連絡をする。連絡をするにあたっては、各支所の支所長に報告し、支所長もしくは副支所長が連絡をする。

・地域住民からの、地域の中で支援が必要と思われる世帯や子どもの安全などについての相談があった場合には、各市町村の民生委員等へ支所長もしくは副支所長が連絡をする。

・住民の方が倒れていた等の場合は、救急車や警察等への連絡を優先し人命の確保を最優先する。

## 成果と課題

## ■成果

・定期的（宅配事業の場合は毎週、夕食宅配の場合は平日毎日）に、同じ職員が配達しており、組合員の暮らしや地域の様子を知っているので「ふだんと違う」ことに気づき、発見する場面が多々発生している。

・協定で、生協が地域社会の安全・安心を守っていく役割を担うことを宣言することで、職員への意識付けや、事態発生時の対応優先、配送業務のフォローなどの職場体制が整えやすくなるという効果がある。

## ☑課題

・生協の宅配は週１回のみなので、他の事業者にもこの協定が広がって、隙間のない見守りを地域の中に作っていけたらよい。

・夕食宅配では、利用者の親族等の緊急時連絡先を集約して、万一のときは連絡できるようにしている。

共同購入事業でも、そのような情報を把握することがさらなる見守りにつながる。

・遠くにいる子どもさんが、ネットで注文して親に商品を届けているケースもある。こうち生協が見守り活動に協力していることをそういう方にも知ってもらって、さらに安心してもらいたいし、頼りにしてもらえる生協になりたい。
■この間の事例

配送担当	いつも荷受けに出てくる人が出てこないので声を掛けたら、室内で脳出血で倒れていた。	娘さんの勤務先に連絡、救急車を呼んだ。
配送担当	いつも在宅の人なのに鍵がかかっていた。近所の組合員さんに鍵を開けてもらったら熱中症で倒れていた。	救急車を呼んだ。
配送担当	家の裏で組合員さんが倒れていた。	救急車を呼び、生協組合員だった娘さんに連絡した。
夕食宅配担当	夕食弁当を冷蔵庫に入れてあげるために室内に入ったら、利用者がトイレで倒れていた。意識あり。	汚物を処理し、娘さんと介護士に連絡した。
配送担当	配送中に自転車の高齢者が倒れるのを目擊。声を掛けたら座り込んで、やがて意識がなくなった。	近くの病院から医者を呼び、AED処置を行った。
夕食宅配担当	利用者が夕食弁当を食べずに手渡しで返してくることが続いた。夜、職員が様子を見に行くと倒れていた。	大家さんを呼んでチェーンを切ってもらって救急車を呼んだ。
配送担当	台風接近時に傘をさして歩いていた高齢の男性が転倒。	救急車を呼んだ。
配送担当	配達先でない家の前で足を滑らせ溝に落ち、起き上がれない高齢男性を発見。	起こして家まで送った。
配送担当	病院の駐車場で、受診の付添いで来ていた高齢女性から、1人で患者を車に乗せることができないから手伝ってほしいと頼まれた。	車に乗せることを手伝った。
夕食宅配担当	足が不自由な方のところへ配達に行くと、中から呼ぶ声が聞こえ、中に入ると、転倒して起き上がれなくなっていた。	起こしてあげた。
夕食宅配担当	届けたお弁当を食べた形跡がなかった。	娘さんに連絡した。
夕食宅配担当	配達先の家の鍵がかかり、新聞が残っていた。	地域包括支援センターに連絡した。(何かあれば包括に連絡することになっていた方)
店舗	高齢夫婦がバックヤードの裏で気分が悪いと歩けなくなっていた。	車で自宅まで送った。
店舗	高齢男性が店舗の前で自転車で転倒、1人では起き上がれなくなっていた。	起こして、自転車を積んで自宅まで車で送った。近所の人に事情を話すと、娘さんに連絡をしてくれた。
店舗	病気持ちの高齢者で体調が悪そうだった。最近は病院にも行っていないとのことだった。	公的機関の健康相談窓口に連絡した。いつでも相談できるようにした。

連絡先 こうち生活協同組合
〒781-0013 高知県高知市薊野中町16-8
TEL 088-826-5211 / URL http://www.kochicoop.or.jp/
# CPRC Discussion Paper Series

# Competition Policy Research Center Japan Fair Trade Commission

# Coverage Area Expansion, Customer Switching, and Household Profiles in the Japanese Broadband Access Market

Mitsuru SUNADA

Competition Policy Research Center,

Japan Fair Trade Commission

Masato NOGUCHI

InfoCom Research, Inc.

Hiroshi OHASHI

Faculty of Economics, University of Tokyo

Yosuke OKADA

Graduate School of Economics,

Hitotsubashi University, and CPRC

CPDP-34-E May 2008

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

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

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

E-mail:cprcsec@jftc.go.jp
# Coverage Area Expansion, Customer Switching, and Household Profiles in the Japanese Broadband Access Market $ ^{*} $

Mitsuru Sunada $ ^{a} $ , Masato Noguchi $ ^{b} $ , Hiroshi Ohashi $ ^{c} $ , and Yosuke Okada $ ^{d} $

May 2008
Coverage Area Expansion, Customer Switching, and Household Profiles in the Japanese Broadband Access Market

## Abstract

This paper examines diffusion process of internet broadband access in Japan by modeling the household choice behavior of broadband access modes, the choice set of which includes dial-up, integrated services digital networks (ISDN), cable television systems (CATV), asymmetric digital subscriber lines (ADSL), and optic fibers (fiber-to-the-home; FTTH). Estimates from random utility model of access demand reveal that characteristics of users, rather than those of access modes, play a significant role in demand substitution across the modes. Simulation exercises indicate that even if FTTH had been made available to the whole country in the year of 2005, merely about 11 percent of households would have switched to the mode. This result implies that inertia to existing access modes is considerably persistent and indirect network effects play an important role in the adoption of the new technology. Policy implications are also proposed.

JEL Classification: L10, L50, L96

Keywords: broadband access; coverage area; household profile; fiber-to-the-home (FTTH); simulation analysis
### 1. Introduction

The rapid expansion of broadband Internet access has been a spectacular phenomenon of the early twenty-first century. The present paper examines diffusion process of internet broadband access in Japan by modeling the household choice behavior of broadband access modes, the choice set of which includes dial-up, integrated services digital network (ISDN), cable television systems (CATV), asymmetric digital subscriber lines (ADSL), and optic fibers (fiber-to-the-home; FTTH). Furthermore, we simulate switches between access modes if FTTH becomes available to households that are currently not covered.

Although the dominant mode of access varies from one country to another, fiber-optic access is a promising mode that permits transmission over longer distances at higher data rates than other forms of wired and wireless communications do. According to OECD (2006), Korea and Japan are prominent among the OECD countries with regard to the penetration rate of optic fibers.

Most previous studies are based on a relatively strong assumption about the substitution patterns among various access modes $ ^{1} $ . In a recent study, Pereira and Ribeiro (2006) employed a more sophisticated demand framework using a random-coefficient logit model. According to Gaynor and Vogt (2003), however, a conventional fixed-coefficient linear random-utility model with rich microdata can be an effective substitute for a random-coefficient logit model to relax the independence from irrelevant alternatives (IIA) restriction on the substitution patterns. Therefore, the present study, with detailed information about household profile and coverage areas of municipalities, adopts a fixed-coefficient linear random-utility model promulgated by Gaynor and Vogt (2003).

Estimates from random utility model of access demand reveal that characteristics of users, rather than those of access modes, play a significant role in demand substitution across the modes. Simulation exercises indicate that even if FTTH had been made available to the whole country in the year of 2005, merely about 11 percent of households would have switched to the mode. This result implies that inertia to existing access modes is considerably persistent and indirect network effects play an important role in the adoption of the new technology. Hence, government policy should focus not only on the expansion of the FTTH coverage area, but also on the enhancement of quality and variety of software associated with FTTH.

The remainder of the paper is organized as follows. The subsequent section briefly reviews the Japanese broadband access market and describes the coverage areas for various access modes among 2,362 municipalities as of 2005. Section 3 describes the data, and Section 4 explains the empirical specifications, variable definitions, and estimation results. Section 5
conducts the simulations regarding the expansion of the FTTH coverage. Finally, Section 6 concludes the paper.

### 2. Broadband Access Services in Japan

#### 2.1. Rapid Growth of Broadband Subscribers in Japan

Figure 1 depicts the Japanese broadband access subscribers from June 2001 to March 2006. The number of FTTH subscribers has rapidly increased since the early 2000s (the average quarterly growth rate was 47%). In March 2006, FTTH subscribers accounted for 23% of the total broadband users. Although the dominant access mode is still ADSL, the growth rate of the ADSL subscribers gradually slowed down in the 2000s. The growth rate of the number of CATV Internet subscribers was considerably slow, and it accounted for 14% of the total as of March 2006.

= Figure 1 =

#### 2.2. NCCs Dominate the Japanese ADSL Market

Figure 2 depicts the market shares of the main carriers regarding ADSL and FTTH as of September 2005. The following points are worth noting. First, contrary to most other advanced countries, new common carriers (NCCs) dominate the ADSL market in Japan. The total share of NCCs was around 60% in September 2005. On the other hand, NTT East and NTT West account for the majority in the FTTH market, and the combined market share of the two NTT subsidiaries is 59%.

Second, FTTH consists of the following two types of access according to housing type: complex housing and detached housing. The salient feature of the complex housing service is the common sharing of an optic fiber among several households, which enables a much lower rate level per user. NTT East and NTT West accounted for 41% of the total subscribers of the complex housing service. Further, note that the corresponding market share of the detached housing was 73%.

= Figure 2 =

#### 2.3. Coverage Areas of Various Broadband Access Modes in Japan

Broadband access services, FTTH in particular, are not available for every household. Figure 3 depicts those municipalities (in black) where NTT’s fiber-optic service (“B FLETS”) was
available as of June 2005 $ ^{2} $ . Table 1 presents the population coverage rate of broadband access in the nine representative regions (i.e., Hokkaido, Tohoku, Kanto, Tokai, Hokuriku, Kansai, Chugoku, Shikoku, and Kyushu). The population coverage of ADSL is more than 80% in almost all regions, whereas the coverage rate of FTTH varies according to the regions.

$$ =Figure3\&Table1= $$

#### 2.4. Probit Analysis on the Coverage Areas of FTTH

In order to check whether there is some correlation between household characteristics and FTTH coverage areas, we employ simple probit regressions using the FTTH coverage data. This information will facilitate our demand specifications in the later sections. The unit of observation is a municipality. A dependent variable is a dummy variable that takes the value of unity if FTTH is available in that municipality as of June 2005, and zero otherwise. The explanatory variables are as follows: (i) ratio of people aged over 65 to the total population, (ii) average number of students per household, (iii) average family size per household, (iv) ratio of single-person households to the total number of households, (v) female ratio to the total population, (vi) home ownership rate, and (vii) household density.

Table 2 presents the estimation results. All the explanatory variables, with the exception of family size and home ownership rate, are statistically significant. The only significant variable with a negative sign is the ratio of people aged over 65. On the other hand, significant variables with positive signs include the ratio of single-person households, the ratio of women, and household density. Contrary to our expectation, the sign of the female ratio is positive and significant.

$$ =Table2= $$

### 3. Brief Description of the InfoCom Survey

#### 3.1. Choice-based Sampling

This paper utilizes a web-based questionnaire survey conducted by InfoCom Research, Inc., (a market research and consulting firm focusing on telecommunications industries) in June 2005 (hereafter, the InfoCom Survey). The InfoCom Survey was conducted by using a choice-based sampling. Benchmarking clusters were residential areas (zip codes), access modes, and Internet telephones. The number of effective responses was 4,917. Since this survey was not strictly
based on a random sampling procedure, it is important to be sufficiently careful about whether our dataset is a representative sample of the general population. For this purpose, we compared our basic data with other relevant government statistics with regard to (i) household size and composition, (ii) population by prefecture, (iii) housing condition, and (iv) access mode. Although the differences between the InfoCom Survey and the relevant government statistics are minimal, we needed to be sufficiently careful about the demand specification as well as the selection of explanatory variables $ ^{3} $ .

#### 3.2. Household Profiles and Internet Usage

It is extremely likely that the choice of access mode is closely associated with the household profile as well as the Internet usage pattern (Rappoport, et al. 2003). Indeed, preference for Internet access varies among households. Table 3 presents some selected facts according to the InfoCom Survey. We rearranged the fifteen alternatives of the survey into the following eight access modes: (i) FTTH for detached housing, (ii) FTTH for complex housing, (iii) High-speed ADSL (at no less than 24 Mbps), (iv) Medium-speed ADSL (at no more than 24 Mbps and no less than 8 Mbps), (v) Low-speed ADSL (at no more than 8 Mbps), (vi) CATV, (vii) ISDN, and (viii) Dial-up. We omitted 1,671 observations due to an inconsistency in the responses and due to incomplete responses on income, family size, etc. As a result, the total number of households used in this study was 3,246.

= Table 3 =

The first panel of Table 3 presents the household profile according to the choice of access modes. Roughly speaking, there are no particular differences based on access modes. It should be noted, however, that the ratio of single female households among the FTTH subscribers is much lower than that of other access modes. For example, the ratio of single female households to the total number of households who subscribe to FTTH for detached housing is 4.5%. In addition, the ratio of households living in a rented housing among the ADSL subscribers is much higher than that of other access modes. The ratio of house-renters to the
total number of households who subscribe to high-speed ADSL is 20.4%.

The second panel of Table 3 presents the usage intensity and history and the ratio of subscribers utilizing various service contents such as shopping, auctions, music, games, and movies. Internet subscribers to FTTH, high-speed ADSL, and CATV are obviously intensive Internet users. Users subscribing to FTTH and high and medium-speed ADSL services tend to enjoy games and movies via the Internet. For example, FTTH subscribers for detached housing use the Internet for 22.8 hours per week on average.

### 4. Estimation of Broadband Access Demand in Japan

#### 4.1. Demand Specification

Household i's indirect utility $ v_{ij} $ that is obtained from subscribing to access mode j is specified as follows:

$$ \begin{aligned}v_{_{ij}}&=V(p_{_{ij}},x_{ij},D_{_{i}}^{^{p}},D_{_{i}}^{^{x}},R_{_{ij}},Z_{_{i}}\mid\theta)+\varepsilon_{_{ij}}=a_{_{ij}}p_{_{ij}}+b_{_{ij}}x_{_{ij}}+R_{_{ij}}\mu+Z_{_{ij}}\gamma+\varepsilon_{_{ij}}\\a_{_{ij}}&=\alpha+D_{_{i}}^{^{p}}\delta+R_{_{ij}}\nu\\b_{_{ij}}&=\beta+D_{_{i}}^{^{x}}\eta+R_{_{ij}}\omega\end{aligned} $$

where p and x denote the price and download traffic speed, respectively. Coefficient a is the marginal utility of income, and b is the marginal utility of traffic speed. We assume that both these parameters depend on the row vectors of sociodemographic variables $ D^{p} $ and $ D^{x} $ . In addition, the marginal utilities of income and traffic speed also vary with row vector R that constitutes the interaction terms between the household's usage pattern and an access mode type. Z is a row vector of the other control variables. The vector of parameters $ \theta = (\alpha, \beta, \gamma', \delta', \eta', \mu', \upsilon', \omega') $ determines the consumer's preference. Finally, $ \varepsilon $ is assumed to conform to type I extreme value distribution.

Given this specification, the probability of household i choosing access mode j is expressed as follows:

$$ L_{ij}(\theta)=\frac{A(i,j)\exp[V(p_{ij},x_{ij},D_{i}^{p},D_{i}^{x},R_{ij},Z_{i}\mid\theta)]}{\sum_{k}A(i,k)\exp[V(p_{ij},x_{ij},D_{i}^{p},D_{i}^{x},R_{ij},Z_{i}\mid\theta)]} $$

where

$$ A(i,j)=\left\{\begin{aligned}&1&&if access mode j&&is available for household i\\ &0&&otherwise\end{aligned}\right. $$
is an index function indicating that access mode j is available for household i. Using this index function, we can explicitly incorporate the coverage area of each access mode into the model $ ^{4} $ .

Based on the above specification, it is straightforward to estimate the preference parameters that maximize the following log-likelihood function:

$$ L L(\theta)=\sum_{i}\sum_{k}I(i,k)\ln L_{i k}\left(\theta\right) $$

where

$$ I(i,j)=\left\{\begin{aligned}&1&&if i choose j,\\ &0&&otherwise.\end{aligned}\right. $$

Using the estimated parameters, the average choice probability of access mode j is defined as follows:

$$ \overline{P}_{j}(\theta)=\frac{1}{N}\sum_{i}L_{ij}(\hat{\theta}) $$

where $ \hat{\theta} $ represents a maximum likelihood estimator. Accordingly, the elasticity of demand for access mode k with respect to the price of access mode j is

$$ \overline{E}_{jk}^{p}=\frac{\partial\overline{P}_{k}(\hat{\theta})}{\partial p_{j}}\frac{p_{j}}{\overline{P}_{k}(\hat{\theta})}\cong\left\{\begin{array}{ll}\displaystyle\frac{1}{N}\sum_{i}a_{i}[1-L_{ij}(\hat{\theta})]\frac{L_{ij}(\hat{\theta})}{\overline{P}_{j}(\hat{\theta})}p_{ij}&\text{if}j=k\\ \\ -\frac{1}{N}\sum_{i}a_{i}L_{ij}(\hat{\theta})\frac{L_{ik}(\hat{\theta})}{\overline{P}_{k}(\hat{\theta})}p_{ij}&\text{otherwise}\end{array}\right. $$

where N is the number of households.

Although our demand specification is based on a simple conditional logit model, the consumer characteristics and interaction terms between the household's usage pattern and an access mode type may produce various substitution patterns that are not subject to the IIA property.

In a similar manner, we define the traffic-speed semi-elasticity that denotes the percentage change in the market share of access mode k with respect to 1 Mbps change in the download traffic speed of access mode j, that is,
$$ \overline{E}_{jk}^{x}=\frac{\partial\overline{P}_{k}(\hat{\theta})}{\partial x_{j}}\frac{1}{\overline{P}_{k}(\hat{\theta})}\cong\begin{cases}\begin{array}{ll}\displaystyle\frac{1}{N}\sum_{i}b_{i}[1-L_{ij}(\hat{\theta})]\frac{L_{ij}(\hat{\theta})}{\overline{P}_{j}(\hat{\theta})}\quad if j=k,\\\end{array}\\\begin{array}{ll}\displaystyle-\frac{1}{N}\sum_{i}b_{i}L_{ij}(\hat{\theta})\frac{L_{ik}(\hat{\theta})}{\overline{P}_{k}(\hat{\theta})}\quad otherwise.\end{array}\end{cases} $$

#### 4.2. Variable Construction

##### 4.2.1. Choice Set and Coverage Area

We set the following seven alternatives for Internet access modes: either (i) FTTH for detached housing or (i') FTTH for complex housing, (ii) high-speed ADSL, (iii) medium-speed ADSL, (iv) low-speed ADSL, (v) CATV, (vi) ISDN, and (vii) dial-up. It should be noted that since we regard the housing types as previously mentioned, we do not allow the two alternatives (i) and (i') at the same time $ ^{5} $ .

We explicitly utilize the information pertaining to the availability of each broadband access mode in the computation of choice probabilities. Our availability information is based on the coverage areas of NTT East and NTT West, with the exception of CATV $ ^{6} $ . Table 4 presents the availability of the eight alternatives by region and city size as of June 2005. About 15% of the households could not subscribe to FTTH services. In particular, in towns and villages, almost 50% of the households live in the areas where FTTH services are unavailable.

$$ =Table4= $$

##### 4.2.2. Price and Download Traffic Speed

Price is defined by the basic monthly charge including an additional fee for the Internet service provider (ISP). Price data is corresponded with a household based on its selected carrier and ISP $ ^{7} $ . With regard to FTTH, ADSL, and CATV services, we obtained the data on price and nominal download traffic speed from InfoCom Research, Inc. The price and speed of ISDN and dial-up services are those of NTT East or NTT West $ ^{8} $ . Table 3 provides the average price and speed for each access mode.
One of the common difficulties faced when using a discrete choice model pertains to the assigning of prices and speeds of other alternatives that are not actually chosen. We assume that each household makes a comparison between a certain access mode and the other alternatives based on regional-averaged price and speed, depending on the location of the household.

##### 4.2.3. Other Control Variables

We include the following sociodemographic variables as control variables: (i) dummy for single female households, (ii) household size, (iii) dummy for a household with a student, (iv) dummy for rented housing, and (v) the municipal population density of each residential area $ ^{9} $ . These demographic characteristics may have some effect on the mean marginal utility of income as well as the mean marginal utility of traffic speed $ ^{10} $ .

Further, we include an NTT-user dummy that takes the value of unity if a household selects NTT's Internet access service from among FTTH, ADSL, and ISDN. In addition, we add the cross term between a CATV-user dummy and prefecture dummies for Toyama, Fukui, and Mie, because these three prefectures have a prominently high penetration rate of the CATV service. Table 5 provides the descriptive statistics of these regression variables.

= Table 5 =

##### 4.2.4. Interaction Effect Variables

According to Table 3, subscribers to high speed Internet access modes, particularly FTTH, tend to use the Internet intensely, and the Internet history of users varies across the different access modes. Hence, these two variables represent the households' preferences with regard to Internet access speeds.

Row vector R in Equation (1) represents the interaction effect between the household's usage pattern and an access mode type that produces various substitution patterns that are not subject to the IIA property. We define the two arguments of row vector R by using the intensity and history of Internet usage as follows. First, we calculate the average usage hours per week and the average usage history in months for each access mode j. Then, we compute the difference between the reported values by each household i as well as the averaged value among households, that is,