Viet-Cuong Ta

Trung-Kien Dao

Dominique Vaufreydaz

Eric Castelli

Smartphone-based user positioning in a multiple-user context with Wi-Fi and Bluetooth

Keywords: indoor localization, indoor navigation, collaborative positioning, Wi-Fi, Bluetooth, smartphone applications

In a multi-user context, the Bluetooth data from the smartphone could give an approximation of the distance between users. Meanwhile, the Wi-Fi data can be used to calculate the user's position directly. However, both the Wi-Fi-based position outputs and Bluetooth-based distances are affected by some degree of noise. In our work, we propose several approaches to combine the two types of outputs for improving the tracking accuracy in the context of collaborative positioning. The two proposed approaches attempt to build a model for measuring the errors of the Bluetooth output and Wi-Fi output. In a nontemporal approach, the model establishes the relationship in a specific interval of the Bluetooth output and Wi-Fi output. In a temporal approach, the error measurement model is expanded to include the time component between users' movement. To evaluate the performance of the two approaches, we collected the data from several multi-user scenarios in indoor environment. The results show that the proposed approaches could reach a distance error around 3.0m for 75 percent of time, which outperforms the positioning results of the standard Wi-Fi fingerprinting model.

Introduction

In a GPS denied environment, Wi-Fi and Bluetooth could be considered as alternative wireless-based solutions for positioning purpose. Novel Wi-Fi-based positioning methods on smartphones can find the position by scanning the available Wi-Fi access points in the surrounding environment. The mean distance error is around 5m [START_REF] Torres-Sospedra | The smartphone-based offline indoor location competition at ipin 2016: Analysis and future work[END_REF], due to the unreliable characteristics of the Wi-Fi signal propagation in indoor environment. In the case of Bluetooth-based positioning, the Bluetooth technology available on smartphones nowadays is much similar to the Wi-Fi technology in terms of underlying radio physical characteristics and application level. Therefore, it is possible to create a positioning system similar to the Wi-Fi ones. However, the Bluetooth communication range is smaller than that of Wi-Fi. To be of interest in a large area, it requires to deploy a high number of static beacons [START_REF] Faragher | An analysis of the accuracy of bluetooth low energy for indoor positioning applications[END_REF].

When several users are present, the Bluetooth data can be joined with the Wi-Fi data to create a collaborative positioning framework. When each user moves with a smartphone in a public area, it is possible to keep the smartphone's Bluetooth in visible mode. Then, if a device sees another device nearby, the Receive Signal Strength (RSS) from Bluetooth data could give an approximation of the relative range between the two devices. Given the estimating pair-to-pair distance, it is possible to refine the output positions from 1 Wi-Fi data. This approach does not require to install additional infrastructures and is compatible with the standard Bluetooth protocol which is generally supported by smartphones.

There are several key challenges of the proposed approach. The first difficulty is the noisy propagation characteristics of radio signals in indoor environment. The noise affects both Wi-Fi output positions and Bluetooth output distances, moreover in the case of moving users. The second difficulty is the missynchronization between the Wi-Fi and Bluetooth scanning processes in the smartphone. In other words, the scanning cycle for each technology in the smartphone are not guaranteed to start and finish at the same time.

In this work, we try to overcome these problems by considering non-temporal and temporal approaches. In the non-temporal approach, the distance error of the Wi-Fi output position is modeled by a Gaussian distribution. Similarly, another Gaussian distribution is used to describe the distance error between two devices from the Bluetooth inquiry process. Wi-Fi and Bluetooth outputs within a short time period are treated as if they happen in a same time window. An error function is then created to measure the mismatch between the two distributions. By neutralizing the mismatch, it is possible to improve the position results of Wi-Fi output. In the temporal approach, the time component of the users' movement is incorporated into the error function. The error function uses the positions of all the users as parameters. We employ particle-filter-based tracking to minimize the error function. The particle filter uses as observation model the combination between Wi-Fi and Bluetooth scanning data. The experiments were conducted with real scenarios with up to four users. Both the non-temporal and temporal approach results are tested against the standard Wi-Fi fingerprinting model. Our results show that it is possible to make use of Bluetooth signal to improve the positioning output of the Wi-Fi fingerprinting model.

The remaining parts of the paper are arranged as follow: in the section II, the related works on smartphonebased indoor positioning and collaborative positioning are introduced. Our approaches for combining Wi-Fi and Bluetooth data are presented in section IV. The experiments and results are carried out in section IV. The section V contains the conclusion and future works.

Related works

The usage of Wi-Fi for positioning is well-studied. Popular approaches included geometry-based approaches [START_REF] Bose | A practical path loss model for indoor wifi positioning enhancement[END_REF][START_REF] Chintalapudi | Indoor localization without the pain[END_REF] or fingerprinting based approaches [START_REF] He | Wi-fi fingerprint-based indoor positioning: Recent advances and comparisons[END_REF]. The fingerprinting based are preferred because it takes benefit from the deployment of WLAN infrastructure. Recently works on smartphone-based with Wi-Fi fingerprinting have reached a mean distance error of around 5m [START_REF] Torres-Sospedra | The smartphone-based offline indoor location competition at ipin 2016: Analysis and future work[END_REF][START_REF] Mathisen | A comparative analysis of indoor wifi positioning at a large building complex[END_REF]. For learning techniques, the well-known K-Nearest Neighbors (KNN) and its alternative are among the most popular technique [START_REF] Ma | An improved wifi indoor positioning algorithm by weighted fusion[END_REF][START_REF] Liu | Smallest enclosing circle-based fingerprint clustering and modified-wknn matching algorithm for indoor positioning[END_REF]. In [START_REF] Torres-Sospedra | Ensembles of indoor positioning systems based on fingerprinting: Simplifying parameter selection and obtaining robust systems[END_REF], the authors differ a wide range of KNN parameters to get a set of models. An ensemble result of the generated KNN models has a mean distance error of around 6m. Besides KNN-based learning methods, decision tree-based learning methods can be used for learning the Wi-Fi signal characteristics with prominent results [START_REF] Ta | Smartphone-based user location tracking in indoor environment[END_REF].

For positioning purpose, Bluetooth technology can be employed in the same way with Wi-Fi technology. Bandara et al. [START_REF] Bandara | Design and implementation of a bluetooth signal strength based location sensing system[END_REF] use up to four Bluetooth antennas as static stations. The proposed system is able to locate a Bluetooth tag within a room with area of 4.5m × 5.5m. The RSSI value is used to classify the tag's position between different subareas of the room. Pei et al. [START_REF] Pei | Using inquiry-based bluetooth rssi probability distributions for indoor positioning[END_REF] employ fingerprinting-based approach to track a moving phone. The setup includes only three Bluetooth beacons in a corridor-like space of 80m long approximately. The horizontal error is reported at 5.1m. For comparison, the Wi-Fi-based solution has an error of 2.2m in the same area. However, these results are possible thanks to the 8 installed WLAN access points. More recent works employ the new BLE technology. The BLE beacons are smaller and more energy efficient. They are able to power up for a longer period of time [START_REF] Gomez | Overview and evaluation of bluetooth low energy: An emerging low-power wireless technology[END_REF]. Thus, they are more convenient to create Bluetooth beacon networks for positioning purpose. Faragher and Harle [START_REF] Faragher | An analysis of the accuracy of bluetooth low energy for indoor positioning applications[END_REF] provide an in-depth study of using BLE for indoor localization purpose. The distance error of Bluetooth-based approach could reach as low as 2.6m for 95% of times. However, a high number of beacons should be deployed to reach the above performance. The study also addresses some issues of the BLE signal such as the scanning cycle, fast fading effects and Wi-Fi scanning interference. A similar performance for BLE-based indoor positioning is reported in [START_REF] Zhuang | Smartphone-based indoor localization with bluetooth low energy beacons[END_REF]. The authors employed fingerprinting-based approach with the RSS value from the installed BLE beacons.

In a scenario involving multiple devices, there are several works on collaborative localization. Those works rely on some specific wireless technologies, which support the peer-to-peer communication. These technologies include Bluetooth, Wi-Fi Direct and Sound. They are capable to discover the existence of nearby neighbors. In [START_REF] Liu | Face-to-face proximity estimationusing bluetooth on smartphones[END_REF], the task of detecting face-to-face proximity is studied. The smartphones are used to scan nearby visible Bluetooth devices in daily usage. From the received RSSI, relative distance between two devices is calculated. The distance is then used to detect whether the two users are closed to each other. To deal with noisy Bluetooth signals, additional techniques such as RSSI smoothing and light sensor data are introduced for calculating a more accurate distance. [START_REF] Jun | Social-loc: Improving indoor localization with social sensing[END_REF] propose the Social-Loc system, which uses Wi-Fi Direct technology for detecting two events: Encounter and Non-Encounter between each pair of users. In their work, the authors find the RSSI peak for separating Encounter and Non-Encounter events. These detected events are then used to improve the Wi-Fi fingerprinting and Dead Reckoning tracking. The drawback of Wi-Fi Direct technology is that it does not allow a regular Wi-Fi scanning. Therefore, the proposed Social-Loc is more suitable for improving the Dead Reckoning tracking than the Wi-Fi fingerprinting tracking. Sound-based ranging is also useful to detect the relative distance between two devices. In [START_REF] Liu | Push the limit of wifi based localization for smartphones[END_REF], the authors use the sound-based distance to improve Wi-Fi fingerprinting-based positioning system. The acoustic ranging is designed with TOA method for calculating the distance between devices. The estimated ranges are then used to form a graph between devices. The graph's vertices are derived from the Wi-Fi positioning output. A search within the graph is then performed to find the best match position. The searching task aims to find an agreement between the vertices' position and the edges' length. The proposed approach has a mean error of around 1.6m, depending on specific setups. However, the study only mentions the cases when all the devices are in static position.

Using Bluetooth Data to Improve Wi-Fi Positioning

Wi-Fi data and Bluetooth data are two data streams which carry different information of users' position. For indoor positioning, the positioning of a user can be derived the Wi-Fi technology by scanning RSS signal of nearby access points. When there are multiple users, the distance from one user to other user can be calculated from the Bluetooth scanning process. A way to combine the two different data streams is to use an additional central server. The server keeps all the available positioning information from each participate devices. More precisely, the information includes the estimated position from Wi-Fi data and the estimated distances between pairs of devices from Bluetooth-data. There are several works in the literature which take the same approach for indoor positioning based on fusing different data streams. For example, [START_REF] Dao | User localization in complex environments by multimodal combination of gps, wifi, rfid, and pedometer technologies[END_REF] uses a server-based solution for combining different information to improve the localization results.

Centralized Positioning Framework with Wi-Fi and Bluetooth

In our task of fusing Wi-Fi and Bluetooth data, two types of required information must be send to the server side. The first type is the scanned Wi-Fi information of access points. For each completed scan cycle, the device sends identifier (Wi-Fi MAC address) of the seen access points and their RSS values. Each scan cycle lasts several seconds and is device dependent. The second type is the Bluetooth scanned information. The scanned information contains the Bluetooth MAC addresses of seen devices and their RSS values. The time of a complete Bluetooth scan is not defined. When a new Bluetooth device is seen, it could be sent to the server immediately. In practice, there can be many visible Bluetooth devices within the environment such as wireless headphones or mice. The server side maintains a list of active devices. From the list, only the Bluetooth information from the participant devices is kept for positioning purpose.

On the server side, the data from Wi-Fi and Bluetooth scans give different ways to calculate the users' positions. Figure 1 illustrates the principle of our approach. For simplicity, we consider the positioning problem within a single floor. Each user is identified by his smartphone. The example context involves two users, namely the i th and j th users. The two users' devices keep gathering Wi-Fi access points data and Bluetooth inquiry data within the environment and send them to the server. The server receives the data and stores them as typed Events (Wi-Fi or Bluetooth). In Figure 1, there are three Events: two Wi-Fi scans and a Bluetooth scan. The real positions of users i th and j th are denoted as (x i truth,t , y i truth,t ) and (x j truth,t , y j truth,t ), respectively. The subscript t is the timestamp. The real distance between the two users is d ij truth,t .

Figure 1: The data send from two devices to the central server and the derived information at the server for estimating each devices' position At time t 1 , one can determine the position of user i th as (x i t1 , ŷi t1 ) from the WLAN scan information of the i th device. The Wi-Fi position output, however, could be different from the real position (x i truth,t1 , y i truth,t1 ) of the user. Similarly, at time t 2 , when the j th device completes a Wi-Fi scan, we can compute the Wi-Fi position output of user j th . Let the result of this computation be (x i t2 , ŷi t2 ). Besides that, the Bluetooth scanning process could give an estimated distance between the two users. At time t 3 , if the two users i th and j th are within the Bluetooth scanning range, we could find the relative distance l ij t3 from the RSS value of Bluetooth scanning process. The value of l ij t3 is an approximation of the real distance d ij truth,t3 between the two users at time t 3 . An alternative way for calculating d ij truth,t3 is using the output position from the Wi-Fi data for both users i th and j th .

In order to benefit from the relationship between Wi-Fi and Bluetooth for improving positioning results, we question two different approaches. The first one is a Non-temporal approach. The temporal relationship between events which are within a time interval window is removed. They are treated as they happened at the same time. The Wi-Fi fingerprinting approach is used for finding user's positioning from Wi-Fi scan. The Log Distant Path Loss (LDPL) model [START_REF] Rappaport | Wireless communications: principles and practice[END_REF] is used to find the distance from the input Bluetooth RSS value. An error estimation function is established by using the users' position as the function's parameters. By minimizing the error function, ir can be used to smooth the mismatch between Wi-Fi data and Bluetooth data, thus, to reduce the positioning error from Wi-Fi. The second approach is the Temporal one. We introduce the time component into the basic error function of the first approach. More precisely, the new error function includes the devices' position at each timestamp. For minimizing the new error function, a particle-based approximation is carried out.

Non-temporal Approach

In the Non-temporal approach, a sliding window of length ∆t is used. All the events from t to t + ∆t are considered to happen at the same time. Given a pair of user i th and j th , one can assume that there exists both Wi-Fi data and Bluetooth data within the time frame from t to t+∆t. Let w i and w j be the Wi-Fi scans from the two users, and rss ij is the RSS value of the Bluetooth scan. In this Non-temporal approach, we remove the time variable t from the parameters. The likelihood function with the two users' position (x i , y i ) and (x j , y j ), and the parameters P (x i , y i , x j , y j |w i , w j , rss ij ), is created by splitting down the function into three separate components:

P (x i , y i , x j , y j |w i , w j , rss ij ) =P W (x i , y i |w i )× P W (x j , y j |w j )× P B (x i , y i , x j , y j |rss ij ) (1)
In the equation, P W (x i , y i |w i ), P W (x j , y j |w j ) are the error estimation from Wi-Fi data of user i th and j th and P B (x i , y i , x j , y j |rss ij ) is the error from the Bluetooth data.

Let (x i , ŷi ) be the computed position from the scan w i . By assuming the distribution of the real position (x i , y i ) to be a 2D Gaussian around the estimated position (x i , ŷi ), P W (x i , y i |w i ), and is measured by:

P W (x i , y i |w i ) ∼ 1 √ 2πδ w e - (x i -x i ) 2 +(y i -ŷi ) 2 2δ 2 w (2)
Similarly, it is possible to compute P W (x j , y j |w j ), given the estimated position (x j , ŷj ) from Wi-Fi positioning models:

P W (x j , y j |w j ) ∼ 1 √ 2πδ w e - (x j -x j ) 2 +(y j -ŷj ) 2 2δ 2 w (3)
To estimate the Bluetooth part of the estimated likelihood, we first calculate l ij from rss ij by using the well-known LPDL model:

l ij = l 0 × 10 rss ij -rss l 0 10n (4)
where rss l0 is the RSS value at the distance l 0 , n is the path loss exponent. The three values rss l0 , n, and l 0 are known constants. The value of l ij is an approximation of the real distance, which comes directly from the real position of users i th and j th , (x i , y i ) and (x j , y j ):

d ij = (x i -x j ) 2 -(y i -y j ) 2 (5)
One can assume that l ij has a Gaussian distribution around d ij , the Bluetooth likelihood can be estimated by another Gaussian kernel:

P B (x i , y i , x j , y j |rss ij ) ∼ 1 √ 2πδ w e - (d ij -l ij ) 2 2δ 2 b (6)
with δ b is a constant indicating the reliability of the LDPL on the RSS Bluetooth signal. From Equations 2, 3 and 4, the likelihood function in Equation 1 could be rewritten as:

P (x i , y i , x j , y j |w i , w j , rss ij ) = C × e -g (7)
with C is an constant, g is a function of x i , y i , x j , y j , and

g = (x i -xi ) 2 + (y i -ŷi ) 2 + (x j -xj ) 2 + (y j -ŷj ) 2 2δ 2 w + ( (x i -x j ) 2 -(y i -y j ) 2 -l ij ) 2 2δ 2 b ( 8
)
For a fast computing of the minimum value of g, two constraints can be added based on the symmetric properties of g. The first constraint is that the four points (x i , y i ), (x j , y j ), (x i , ŷi ), (x j , ŷj ) are aligned. The second constraint is that the distance between (x i , y i ) and (x i , ŷi ) and the distance between (x j , y j ) and (x j , ŷj ) are equal. The function is then rewritten as a function of the distance r between (x i , y i ) and (x i , ŷi ), whose minimum value can be easily computed.

g(r) = r 2 δ 2 w + ( dij -2r -l ij ) 2 2δ 2 b ( 9
)
The removing time information of the incoming Wi-Fi and Bluetooth data make the error probability can be approximated by the function g. However, it introduces several drawbacks. The first one is due to the users' movement. In different time windows ∆t, the Wi-Fi position and the Bluetooth-based distances are variable. The second drawback is the difficulty to determine the time interval length ∆t for grouping consecutive Wi-Fi data and Bluetooth data. The later temporal approach is designed to overcome those drawbacks of the non-temporal approach.

Temporal Approach

In our Temporal approach to the problem, we attempt to use the temporal relationship in the likelihood function P . Instead of relying only on the position of two users at specific timestamp to measure the errors, the likelihood function could be extended to include the moving path of all the users. Each moving path is considered as a sequence of points. The new likelihood function would receive all the points as parameters.

We first construct the likelihood function F , which is a more complete form of P that bases on three probability functions. A motion model M is used to establish the relationship between the position at time t and the position at time t + 1 when the user moves within the area. A probability distribution function W describes the distribution probability from Wi-Fi scan results. The B function describes the distance distribution based on the Bluetooth RSS value from each pair of devices.

Let assume that there are N users to track in T seconds. The time component is added to the position of user i th at time t as (x i t , y i t ). Normally, we can select the time delta value based on the specific purpose of the positioning system. For modeling purpose, it is required that the time index t contains all the event timestamps from Wi-Fi and Bluetooth of all the participant devices. Approximately, all the float-typed timestamps could be rounded to the nearest integer values. The motion model for each user i th is defined as a probability function between the previous position and the present position, M (x t , y t |x t-1 , y t-1 ). The moving component for T seconds for each user i th is then calculated by:

F M i = T t=1 M (x i t , y i t |x i t-1 , y i t-1 ) (10)
For each specific user i th , assuming that there are K timestamps within the T seconds which have the Wi-Fi scan results. One can set the timestamps for Wi-Fi events as u 1 ,u 2 ,...,u K . Then for each u k , the Wi-Fi data is denoted as w ( u k ) i , the function W is used to estimate the likelihood probability W (x i u k , y i u k |w i u k ). Then, the Wi-Fi component F W i of the user i th is built from all the available K Wi-Fi scans:

F W i = K k=1 W (x i u k , y i u k |w i u k ) (11)
The Bluetooth evolves for a specific pair of user i th and user j th . Assuming that there are L Bluetooth data which arrive at timestamps v 1 ,v 2 ,...,v L , it is possible to chain the error function over the L timestamp as follow:

F B ij = L l=1 B(x i v l , y i v l , x j v l , y j v l |rss ij v l ) (12)
By joining the three functions, the total likelihood function F could be written as:

F = ( N i=1 F M i )( N i=1 F W i )( N i=1,j=1 F B ij ) (13)
At this step, one could select the explicit form of M , W and B and process them to find the maximum value of F . The number of estimated parameters in F totally depends on the number of users and the tracking time. As the F function includes a motion model M , particle filter-based approximation is a natural way for approximating the maximum value of F . In addition to that, the particle filter process would have a more flexible way for selecting the explicit forms of W and B. For each user i th at time t, there is a set of particles S t i , which represents the position distribution probability. For the motion model M , without the additional information from inertial sensors, the movement of the user could take random values as the moving speed v and the heading direction h. While there is no constraint on the value of h, the moving speed v should be suitable with a typical indoor movement. In our specific implementation, we generate the moving speed from a normal distribution around a speed average value. The speed average is chosen according to the walking action in indoor environment. The heading is generated from the uniform distribution in the range [0, 2π]. An additional wall-crossing checking step is added for removing bad particles. Figure 2 gives an example of the motion model M for generating the new particles. The center black dot is the initial particle. The walls are represented with black lines. New particles are then generated with a normal distribution moving speed around the speed average value and a uniform heading direction. The green particles are kept. The gray ones, which cross the wall, are removed.

With the particle filter-based approximation, the likelihoods given by Wi-Fi component F W and Bluetooth component F B could be transformed into an observation model. The score a specific p t i ∈ S t i is calculated by: score(

p t i ) = score W (p t i ) + score B (p t i ) (14)
with score W (p t i ) is the Wi-Fi component and score B (p t i ) is the Bluetooth component. If there exists a Wi-Fi scan w at time t, the score W (p t i ) is then computed by using a local estimation on the probability output of Wi-Fi fingerprinting model. The area is first divided into separated clusters, C 1 , C 2 , ...,C D . Using the clusters, we can transform the Wi-Fi fingerprinting model from a standard regression problem into a classification problem [START_REF] Ta | Smartphone-based user location tracking in indoor environment[END_REF]. Let prob w = {a 1 , a 2 , .., a D } is the chance of the predicted output of w belong to the clusters. score W (p t i ) can be computed as followed:

score W (p t i ) = D i=1 score Ci (p) (15)
where score Ci (p) is a scaled-value from prob w , with respect from the maximum distance dmax Ci and minimum distance dmin Ci to all the available particles:

score Ci (p) = a i × (1 - d(p, C i ) -dmin Ci dmax Ci -dmin Ci ) (16)
A constant ∆ 1 t is the effective window length for each Wi-Fi scan.

Similarly, the score B (p t i ) can be calculated if there is any Bluetooth scan involving the user i th around time t. Without loss of generality, we assume that the available Bluetooth scan is rss t ij that specifies the

score B (p t i ) = p t j,k ∈S t j score W (p t j,k ) × B(p t i , p t j,k |rss t ij ) (17)
The subscript k indicates the need to calculate repeatedly for each p j,k ∈ S t j . The likelihood B(p t i , p t j,k |rss t ij ) is computed by using similar process as the computation of the likelihood P B in the Non-temporal approach. Using the Equation 6, the likelihood B can be rewritten as a function of the distance d is the distance between two particles p t i , p t j,k and the distance l is derived from rss t ij by the LDPL model. A constant ∆ 2 t is added to define the effective interval length for a Bluetooth scan.

Experiment and Results

Experiment Setup

To evaluate the performance of the two proposed approaches, we setup an experiment within an office environment which includes two floors. All recordings follow one common trajectory which is composed by the corridor, office rooms and stairs. This trajectory is defined by several checkpoints. The path is illustrated in Fig. 3. The length of the path is approximately 200m, which usually takes about 300s of walking at an average speed.

Different scenarios were designed in such a way that the additional Bluetooth scanning data could provide useful information for smoothing the Wi-Fi positioning output. Each of them involves groups of 2 to 4 users. The users were instructed to carry the devices and move around the experimental area. They walk along the same path, with different relative distances between each other. In the recordings, we used an interval of 0.5s for tracking the users. Each time a checkpoint is reached, the time is registered. The checkpoint's position and its reaching time are then used to calculate the user's trajectory as the ground truth movement.

We selected four devices including two smartphones and two tablets for the positioning scenario (see table 1). Each device is set to scan Wi-Fi access points and available Bluetooth devices in the environment. All of them run Android operating system and use the same application for collecting the Wi-Fi and Bluetooth data.

Three approaches are used to localize the users when they are moving within the area: Wi-Fi only (for comparison), Non-temporal and Temporal. In the Wi-Fi only approach, the output of Wi-Fi fingerprinting method is provided as the reference tracking results. First, the data is collected over the walking path. A Random Forest (RF) regressor model is trained on the collected data, using the method described in [START_REF] Ta | Smartphone-based user location tracking in indoor environment[END_REF]. In the testing phase, with each completed Wi-Fi scan from the tested devices, the RF model is used to produce the position output.

In the Non-temporal approach, firstly, the output positions from the pre-trained RF regressor model on Wi-Fi are calculated for each device. If there is any Bluetooth data available, the Bluetooth scanned information is used for adjusting the positions of two involved devices. To solve the problem of non-simultaneous events between Wi-Fi scans and Bluetooth scans, we use a time window of length ∆t = 10 seconds for grouping successive events into the same timestamp. The resulting position is calculated as the mean value of these positions.

In the Temporal approach, a RF classifier model is built on top of the RF regressor model. To transform the real world coordinates to label index, we perform a K-means clustering of all the available training positions from the training data. The new learning targets are the indices of the corresponding clusters. In

Results and Discussion

The tracking results of three discussion approaches are illustrated in the Table 2. In the "one group" setups, every user is instructed to move as a group throughout the corridors. In other configuration, users are instructed to move with a distance under 10m to each other. The special case is with 4 users: there are 2 groups of 2 users, which let the system use Bluetooth data to identify both closed and distant devices. The results are reported as the mean average distance errors across all the testing devices in the specific scenario.

The Wi-Fi Only approach reaches a stable performance of under 4.0m in mean distance error. Both Non-temporal and Temporal approaches have better results than the Wi-Fi Only approach. However, the Non-temporal approach's results are not as stable as the Temporal one. In the setup where the users' distance could change within a specific time interval, the Non-temporal approach has similar performance as the output from the Wi-Fi fingerprinting model. In this case, it raises the difficulty to measure the distance in the Equation 5. Meanwhile, the Temporal give a more stable performance. It can decrease the errors from 25% to 50% based on specific testing setups. The biggest relative improvement is the setup of three users moving in one group.

Figure 4 illustrates the distance error for three approaches over all the scenarios. Both the Wi-Fi Only and the Non-temporal have a closed performance. For 75% of times, the distance errors of two approaches are around 5m. The Bluetooth-based relative distance are employed more efficiently in to Temporal approach. It has a significant improvement from the Wi-Fi-based tracking. For 75% of times and 90% of times, the errors of Temporal approach stay around 3.0m and 5.0m, respectively. Beside the Bluetooth information, adding of map-based information and moving model constraint also reduce noisy output from the standard RF Wi-Fi fingerprinting model.

Individual distribution error for each tested device is given in Figure 5. Both smartphones, Samsung Galaxy Note 4 and HTC One ME, have a similar distribution. The Non-temporal approach presents a slightly improvement from using only Wi-Fi data and the temporal approach can reduce the error significantly for the regions less than 7.5m. However, the addition of Bluetooth data does not help when the tracking errors exceed 7.5m. The errors of all three models are distributed similarly at the error regions larger than 10m. It even adds more noise to the tracking results of Device 2. In the case of Device 3 and Device 4, both Non-temporal and Wi-Fi Only have nearly identical distributions and the temporal one outperforms the two others. The Temporal has the highest improvement with Device 4, which can overcome the issue of non-training data.

Conclusion

In this work, we have presented a collaborative tracking framework based on the smartphone's Wi-Fi and Bluetooth scanning data. The Wi-Fi data is used as a raw positioning output, which is then improved by the relative distance from Bluetooth inquiry RSS signals. Two combination approaches are introduced, which is the Non-temporal approach and Temporal approach. The Non-temporal approach attempts to simplify the information fusion task by removing the time-relationship between different Wi-Fi scan and Bluetooth scan.

The Temporal approach takes a more direct way to establish the conditions between the two types of data. Both approaches have been tested and compared with the standard Wi-Fi fingerprinting model. From the testing results, while the Non-temporal is only applicable in some specific scenarios, the Temporal approach outperforms the Wi-Fi fingerprinting models significantly. This study has shown that the collaborative positioning based on the Wi-Fi and Bluetooth data would be applicable in a multi-user context. Combining two type of wireless data can reduce the noise from Wi-Fi fingerprinting model significant. However, the testing scenario are still dealing with simple contexts of multiple users. There are also some remaining issues on the technical aspects, such as the communication between the users and the server, energy impact on the smartphone and signal inference between multiple devices.

Figure 2 :

 2 Figure 2: A simple moving model with the black dot is the initial particle.

Figure 3 :

 3 Figure 3: The moving path, colored in blue color, which includes two floors. The checkpoints are numbered along the moving path.

Figure 4 :

 4 Figure 4: Cumulative distance errors for three approaches

Figure 5 :

 5 Figure 5: Cumulative distance errors for each testing devices

Table 1 :

 1 The four participated devices in the testing scenarios the device i th and j th . The update rule for score B (p t i ) is defined as follow:

	Device ID	Name	Type
	1	Samsung Galaxy Note 4 Smartphone
	2	HTC One ME	Smartphone
	3	Asus ME	Tablet
	4	Samsung Galaxy Tab	Tablet
	RSS value from

Table 2 :

 2 Positioning errors as averages among different devices in several contexts, where the users are asked to move in different groups = 30 for clustering all the available points in the tested area. The radius of each cluster in this configuration is 4.0m approximately. The probability output of the classifier model is then used to update the Particle Filter within a time window of 10 seconds. If there are multiple completed scans within this time window, the nearest completed scan is selected. The Bluetooth data has the effective range set to 2.0 seconds. For the moving model, the average speed of each particle is set to 1m/s. In the simulation step, the number of particles is set to 1000.

	N of Users Groups N of	Wi-Fi Only Non-temporal	Temporal
	2	1	3.7m ± 2.0m	2.4m ± 1.6m	2.2m ± 1.5m
	2	2	3.4m ± 2.4m	3.2m ± 2.3m	2.5m ± 2.0m
	3	1	4.0m ± 2.4m	3.5m ± 2.2m	2.1m ± 1.8m
	3	3	3.6m ± 2.1m	3.1m ± 2.2m	2.2m ± 1.9m
	4	1	3.8m ± 2.6m	3.6m ± 2.6m	2.8m ± 2.0m
	4	2	3.8m ± 2.4m	3.5m ± 2.3m	2.6m ± 2.1m
	our experiments, we use K

Acknowledgement

This publication is part of the output of the ASEAN IVO project IoT System for Public Health and Safety Monitoring with Ubiquitous Location Tracking.


Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies Case of Nikkei Index 400

Keywords: Stakeholder Value, Shareholder Value, Corporate Governance, Labor, Nonregular Employment -JEL Codes: D02, G38, J21, P16

This paper aims at finding out how the shareholder-value pursuit has affected labor policies at large Japanese listed enterprises. It concentrates on the issue of labor bifurcation, whereby the proportion of nonregular employees has grown rapidly over the last two decades, currently approaching the numbers of regular employees.

In Japan, corporate governance reforms became key to structural macroeconomic changes according to the 2013 "Japan Revitalization Strategy" formulated by the Cabinet Office. This document mandated the creation of the JPX-Nikkei Index 400 -an index called to accommodate the most investor-friendly joint-stock companies. The move towards a shareholder model has been further reinforced through a rapid surge in foreign stockholding that started during the post-bubble period of the mid-1990s. At the same time, the externalities of increased returns to stockholders have been the changes in the related domains of management and labor, which I explain through the application of the political economic theory. This theory underlines the importance of inclusion into a "political bloc" for being eligible for economic benefits. Consequently, I argue that increased returns to politically privileged shareholders have been achieved at the expense of a growing proportion of unprivileged nonregular employees.

The evidence yields support to the argument about the positive correlation between shareholder value and the proportion of nonregulars. On the other hand, foreign stockholding does not appear to be significantly correlated with the increase in nonregular employment. In turn, the study has found that the proportion of nonregular employees is significantly correlated with domestic ownership that characterizes higher managerial entrenchment.

Introduction

With the current proportion of nonregular employees in Japan reaching 37.2 percent -a tremendous surge compared with 15 percent in early 1980s -this poses several social and economic challenges to the country (Labor Force Survey, 2017; Figure 1). Nonregular employment should ideally aim at aiding the economy in times of crisis. Otherwise, flexible employees should have prospects of attaining a regular status. This is not the case in Japan, as the chances of this growing labor cohort to become full members of their companies are significantly lower, compared to other developed countries [START_REF] Aoyagi | Labor Market Reform: Vital to the Success of Abenomics[END_REF]. According to the Ministry of Health, Labour and Welfare (MHLW) survey ( 2016) and Labour Force Survey (2017), the average possibility for males to move from nonregular to regular employment in the first quarter of 2016 was six percent, and for females -2.7 percent. Flexibilization of labor is not a problem per se, if it exists in the environment with low labor turnover costs and representative unions, as in Nordic countries, also characterized by coordinated corporate governance [START_REF] Witt | Varieties of Capitalism and institutional comparative advantage: A test and reinterpretation[END_REF]. Contrary to that, Japan has not yet developed robust institutional mechanisms for protecting workforce not affiliated with a company on a long-term basis. Due to emerged gap between regular and nonregular employees, scholars observe rising poverty rate and wage insecurity leading to depressed domestic consumption, which deteriorates private sector accounts [START_REF] Gordon | New and Enduring Dual Structures of Employment in Japan: The Rise of Non-Regular Labor, 1980s-2010s[END_REF]. Another social consequence for nonregulars that follows is a falling confidence resulting in low degrees of marriage. This has wider repercussions by causing a plunge in birthrates [START_REF] Gordon | New and Enduring Dual Structures of Employment in Japan: The Rise of Non-Regular Labor, 1980s-2010s[END_REF]. Finally, as Japanese society ages, growing numbers of precarious workers lead to diminishing social insurance contributions making elderly people more vulnerable [START_REF] Osawa | Precarious work in Japan[END_REF].

Before 1984, when the share of nonregular employees in Japan was less than 15 percent, the voice of regular employees could be considered as roughly representative of the whole labor segment. However, as temporary workforce has been growing steadily since early 1980s, when their numbers were six million, they have reached over 20 million in 2017 (Labor Force Survey, 2017). Nonregular camp is nowadays composed of following categories: part-time workers (49 %), temporary workers / arubaito (21 %), contract employees (14 %), dispatched workers (6 %), entrusted employees (6 %) and others (4 %) (Labor Force Survey, 2017; Figure 2). Concurrently, numbers of regular workforce did not fluctuate significantly -the change has been from 33.3 million in 1984to 33.85 million in 2017(Labor Force Survey, 2017). Based on this evidence, [START_REF] Gordon | New and Enduring Dual Structures of Employment in Japan: The Rise of Non-Regular Labor, 1980s-2010s[END_REF] concludes that the overall 35 percent increase in Japan's working population during the last 30 years is mainly due to the mentioned 14 million surge in nonregular workforce. This number can appear striking granted the fact that Japan's total population has increased during the same period only by 6.46 million people (from 120.3 to 126.76 million) (Japan Statistical Yearbook, 2017). This seeming paradox can be explained by "a sharp contraction of Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies self-employment and family labor, a rise in the numbers of the elderly and the proportion seeking work, and the increase of job-seeking women previously not in the wage labor force expanded the supply available for nonregular jobs" (Gordon, 2017, p. 16). Hence, the Japan's labor change over the last three decades can be summarized as the creation of numerous nonregular positions against the freeze in the hiring of regular employees. This paper attributes the changes in human resource management (HRM) to the growing priority of the shareholder value pursuit by corporate managers. Although CEOs of large Japanese firms continue bearing monitoring functions, which protects them from immediate market-caused distortions, they also tend to become more focused on corporate profitability at the expense of growth. Managers have partially lost their immunity given by relational bank supervisors and have become increasingly subject to shareholders' pressure. In the resulting attempts to guarantee high share-value returns to investors, managers have tended to resort to corporate restructuring [START_REF] Morgan | Shareholder Value in the Japanese Context[END_REF][START_REF] Miyamoto | Change and continuity in Japanese corporate reform[END_REF].

Literature Review

On the international level, Darcillon (2015) establishes a positive correlation between preferential shareholders' treatment (independent variable) and worsening conditions of blue-collar labor (dependent variable) across OECD states. [START_REF] Dore | Financialization of the Global Economy[END_REF] asserts the link between growing shareholders' power and decreased employees' tenure resulting from the intensified pressure from investors. [START_REF] Van Der Zwan | Making sense of financialization[END_REF] underlines ideological nature of financial reorientation towards shareholders that represents capitalist control mechanism. [START_REF] Aglietta | Shareholder value and corporate governance: some tricky questions[END_REF] describes a tendency towards labor bifurcation in the US, whereby lower remuneration for core as well as flexible employees is compensated in relation to the former group through stock-options' provision. Through application of institutional complementarity model, [START_REF] Amable | How do financial markets affect industrial relations: an institutional complementarity approach[END_REF] link low pressure from capital markets to cooperative management-labor bargaining and vice versa. This view is based on the notion that long-term "company-growth" strategy usually results in lower stock prices making a firm subject to potential hostile takeovers. Therefore, such strategy is more efficient and safe under low dependence on market, which is the case of bank finance as opposed to equity finance. Contrary to that, shareholder-oriented companies are subject to more immediate challenges that require focusing on profitability rather than long-term growth. Under these circumstances, management would be less willing to reinvest profits into corporate growth in general and to allocate it to employees (Höpner, 2005).

The literature on corporate financialization establishes a link between the relative growth of financial profits on one hand, and the widening income gap as well as the absence of wages' increments on the other [START_REF] Palley | Financialization: what it is and why it matters[END_REF]. As the goals of companies become more finance-oriented, managers tend to concentrate on short-term market-based criteria, while Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies neglecting firm-specific intangible assets (Gospel & Pendelton, 2003). This is likely to result in the lack of attention to human resource development. [START_REF] Stockhammer | Financialization and the global economy[END_REF] mentions the increase in so-called "rentier income" that includes interest, dividend payments and bonuses, which is associated with the decline in labor costs.

As regards Japan, a systemic view on the roots of the growing proportion of nonregular employees can be captured by the "institutional complementarity" hypothesis. According to one of the general definitions provided by Crouch (2005, p. 359), it refers to a situation "where components of a whole mutually compensate for each other's deficiencies in constituting the whole". Masahiko [START_REF] Aoki | The contingent governance of teams: Analysis of institutional complementarity[END_REF], who was the first to formulate the hypothesis, used it for explaining the institutional fit between contingent monitoring conducted by main banks and long-term employment relations in Japan. It is central to this paper due to its ability to capture the link between shareholder value pursuit and labor deregulation. In agreement with this thesis, the predominance of the in-house careers and the resulting high cost of job loss are institutionally complementary with long-term commitments toward employees [START_REF] Tohyama | Labor and financial-market risks and welfare spending: a comparative study with a special emphasis on Japan[END_REF]. At the same time, those Japanese companies that have been most eager to implement shareholder-oriented policies since 1990s, have loosened employment guarantees [START_REF] Jacoby | The Embedded Corporation: Corporate Governance and Employment Relations in Japan and the United States[END_REF]. In order to both preserve institutional integrity and to pay tribute to shareholders' interests, employers have combined the retained guarantees for the core workforce with increased number of nonregular employees. By breaching the formerly encompassing management-labor compromise, directors have thereby discouraged employees from demanding the expansion of welfare spending [START_REF] Tohyama | Labor and financial-market risks and welfare spending: a comparative study with a special emphasis on Japan[END_REF].

The Japanese Institute for Labor (2010) also highlights the connection between growing shareholders' pressure and incremental change in the HRM, whereby seniority-merit and long-term employment are likely to decrease. [START_REF] Dore | Shareholder capitalism comes to Japan[END_REF] comes up with the argument about fundamentally conflicting interests of shareholders and employees resulting from the ongoing reform. [START_REF] Jackson | Employment Adjustment and Distributional Conflict[END_REF] formulates a similar thesis about an increasing role of market for corporate control in the shrinking proportion of core employees. Watanabe (2015, p. 59) applies an integral framework, arguing that financial / corporate deregulation on one hand, and labor deregulation on the other, are inseparable parts of a strategy aimed at "increasing functional flexibility and lowering production costs". [START_REF] Abe | Corporate finance and human resource management in Japan[END_REF] show the complementarity between firm-centered employment and bank finance on one hand, and individual-centered employment and stock finance on the other. [START_REF] Conrad | From seniority to performance principle: The evolution of pay practices in Japanese firms since the 1990s[END_REF] considers the possibility of shareholder-oriented reforms' resulting in a spread of pay-perperformance system, however does not come up with a definite conclusion. CEAFJP DISCUSSION paper series #18-01

Research Operationalization: Shareholder Value and Nonregular Employment

Research Question: What has been the impact of shareholder value (SV) pursuit on labor policies of Nikkei Index 400 companies? Literature gap. Available scholarship has not come up with robust explanations that would account for Japan's institutional features. In other words, existent literature does not provide a satisfactory answer to the question of why Japanese employers have decreased labor costs not through massive layoffs and overall flexibilization of labor conditions (which is the case of neoliberal policies in the West), but through increasing the proportion of nonregular employees amid retention of preferences for core workers. The basic answer is a tactic of killing two birds with one stone: preserving institutional integrity while at the same time paying tribute to shareholders' interests. Among the few studies that address this problem from institutional and political angles are [START_REF] Peng | Economic Dualization in Japan and South Korea. The Age of Dualization: The Changing Face of Inequality in Deindustrializing Societies[END_REF], [START_REF] Song | Economic distress, labor market reforms, and dualism in Japan and Korea[END_REF], Thelen & Kume (1999;[START_REF] Thelen | Coordination as a political problem in coordinated market economies[END_REF] and [START_REF] Yun | Does 'Driving Range' Really Matter? The Hidden Cost of Internal Combustion Engine Vehicles and the Potentially New Value Proposition of Electric Vehicles: Two Cases from Countryside and Urban Side of Japan[END_REF]. I take the following argument of Song (2012, pp. 416-417) as a starting point: "in Japan, political coalitions between conservative policymakers, large firms, and core regular workers were the driving force of the reinforcement of dualism and inequality by shielding labor market insiders from the pressure for regulatory reforms but extensively eroding regulations protecting outsiders for flexibility".

Suggested contribution. The offered theory is a political economic analysis of institutions. It is particularly well-suited for explaining institutional change like the one where elements of shareholder model are adopted in a stakeholder environment [START_REF] Jackson | Toward a Conceptual Framework for Understanding Institutional Change in Japanese Capitalism: Structural Transformations and Organizational Diversity[END_REF]. Political economic approach defines institutions as "political compromises among different interest groups that form socio-political coalitions to advance their interests" (Lechevalier et al., 2016, p. 6). It has been very recently that [START_REF] Yamada | The Theory of Regulation in Times of Crises -International Conference Research & Regulation[END_REF] as well as [START_REF] Lechevalier | Financialization and industrial policies in Japan and Korea: Evolving complementarities and loss of institutional capabilities[END_REF] and [START_REF] Jackson | Toward a Conceptual Framework for Understanding Institutional Change in Japanese Capitalism: Structural Transformations and Organizational Diversity[END_REF] have demonstrated the merits of applying political economic theory to the issue of intensified SV pursuit in Japan and its connection to labor deregulation. While their analysis is yet preliminary, current research incorporates and tests the view about the pursuit of SV being a political project aimed at power accumulation [START_REF] Amable | Institutional complementarities in the dynamic comparative analysis of capitalism[END_REF].

There are basically two different approaches to SV. One (1), advocated by agency theory representatives [START_REF] Friedman | The Social Responsibility of Business is to Increase its Profits[END_REF][START_REF] Jensen | Theory of the firm: Managerial behavior, agency costs and ownership structure[END_REF][START_REF] Rappaport | Creating shareholder value: the new standard for business performance[END_REF][START_REF] Stewart | The quest for value[END_REF], argues that a joint-stock company is solely a property of its stockholders. The function of managers-agents is to maximize SV under contractual obligations toward stockholders-principles. However, large Anglo-Saxon corporations are characterized by dispersed shareholding, which precludes investors from influencing the voting process at annual general meetings (AGMs). Instead, they can exercise their rights via the ability to sell their stock to an outside bidder. On the other hand, as managers become more autonomous, they claim higher rewards and credentials. If this is achieved at the expense of shareholders' returns, their actions are believed to cause "agency costs". To lower them, stock-listed companies must comply with internationally accepted accounting standards.

Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies Japanese stock-listed companies have been advised to use International Financial Reporting Standards (IFRS) by the Tokyo Stock Exchange in 2010. As of June 2017, 150 companies have decided or planned to adopt IFRS [START_REF] Jpx | Voluntary Application of IFRS (Current and scheduled)[END_REF]. Thereby, even under the absence of direct shareholders' supervision, CEOs are pushed to achieve higher returns to shareholders to sustain a competitive race. Thus, agency theory emphasizes a dogmatic task of CEOs to maximize SV, which is believed to be a primary task of a joint-stock company.

Since outside directors do not play a substantial role in Japan's corporate governance (only 2.5 percent of TSE 1st and 2nd section companies have adopted a U.S.-style "company-with-three-committees" that requires the majority of outside directors), Japan is a good case study to test the effects of SV implementation through accounting metrics. Japan Revitalization Strategy (2013) stresses the foundational role of Return on Equity (ROE) as a crucial index to be pursued by managers for improving corporate productivity. [START_REF] Inagami | The new community firm: Employment, governance and management reform in Japan[END_REF] found out that Japanese CEOs are giving increasing priority to ROE due its ability to capture the efficiency of capital use against shareholders' investment. Therefore, according to Ito (2014, p. 56), "ROE improvement can be regarded as the core of the third arrow of Abenomics". Although there is a clear awareness of the ongoing prioritization of ROE for Japanese stock-listed companies [START_REF] Milhaupt | Evaluating Abe's Third Arrow: How Significant are Japan's Recent Corporate Governance Reforms?[END_REF], agency theory does not question the implications of increased shareholder returns for labor policies.

Sato [START_REF] Aglietta | Shareholder value and corporate governance: some tricky questions[END_REF], cited in Inagami & Whittaker, 2005) measured the influence of ROA and EVA (economic value added) on lifetime employment policy but did not touch upon the issue of nonregular employment. One possible reason for the neglect of this aspect is that drastic increase in temporary employment occurred mainly during the recent decade and was quite a novel issue back in 2000. Another explanation is the problem of collecting data on nonregular employment, which is a significant impediment for the labor-related research (Lechavalier et al., 2014). Listed companies have started to publish the respective data only from 2008. Furthermore, it has been included into financial databases only from 2010. While the levels of SV are not the indicators of sustainable corporate growth, they nevertheless matter for market evaluation and, therefore, reputation of a firm. The following hypothesis aims to link SV with nonregular employment. H1. Higher levels of SV are associated with higher proportions of nonregular employment.

The second (2) view on SV is more comprehensive. According to it, SV has become a contested concept due to widespread attempts to adhere to its standards by coordinated market economies (CMEs) of continental Europe and East Asia [START_REF] Jürgens | Shareholder Value in an Adverse Environment: The German case[END_REF]. The pursuit of SV as a primary goal of a public company in the Anglo-Saxon context is very different from the stakeholder model of corporate governance (CG) of CMEs that considers interests of "shareholders, employees, creditors, customers, and the society in which the corporation resides" (Fiss & Zajac, 2004, p. 501). Thus, managerial merits under stakeholder model are not confined to SV returns. Moreover, managers experience less pressure from capital markets: their motivation rather stems from long-term commitments to company. On contrary, CEOs in the shareholder model are mainly disciplined by the threat of hostile takeovers if they fail to meet investors' demands [START_REF] Deakin | The coming transformation of shareholder value[END_REF]; Mitchell et CEAFJP DISCUSSION paper series #18-01 al., 2005). As a result, while following the task to raise SV, managers commonly resort to restructuring through labor cuts (Darcillon, 2015). Against these societal externalities, there is a logical question about reasons for introducing shareholder features to stakeholder model. A possible prerequisite is a crisis of a national CG, which requires an adoption of a popularly-acclaimed alternative [START_REF] Yoshikawa | Corporate governance reform as institutional innovation: The case of Japan[END_REF]. In the case of Japan, sufficient analysis of compatibility with local institutions is often missing.

The salient stakeholder features of the local CG give yet another reason to critically examine the adoption of SV in Japan. Several studies confirm negative correlation of the SV pursuit and labor costs in Japan. [START_REF] Dore | Financialization of the Global Economy[END_REF] asserts the link between growing shareholders' power and decreased employees' tenure resulting from the intensified pressure from investors. Those Japanese companies that have been most eager to implement shareholder-oriented policies since 1990s, have loosened employment guarantees due to ascendance of SV along the hierarchy of corporate priorities [START_REF] Jacoby | The Embedded Corporation: Corporate Governance and Employment Relations in Japan and the United States[END_REF]. Whereas in the postwar period "the relationship between workers and managers was primary, and that between shareholders and managers was secondary", this order has been reversed from the late 1980s (Yamada & Hirano, 2015, p. 14). Against economic slowdown in 1990s that followed the bubble burst, employers and business have eventually pushed for abandoning the annual negotiations with labor through shunto rounds [START_REF] Uemura | Institutional Changes and the Transformations of the Growth Regime in the Japanese Economy: Facing the Impact of the World Economic Crisis and Asian Integration[END_REF], which caused steady decrease in welfare spending [START_REF] Tohyama | Labor and financial-market risks and welfare spending: a comparative study with a special emphasis on Japan[END_REF].

To incorporate the political dimension into the analysis of SV repercussions for labor, I inquire, in whose interest the enhancement of shareholders' rights is. As already mentioned, CG reforms are a part of the governmental agenda, formulated in Japan's Revitalization Strategy (JRS) (2013). Therefore, CG changes promoted by the Cabinet Office are likely to influence the achievement of higher SV returns. According to the government's view, the targeted companies are primarily the ones included into the Nikkei Index 400 created in 2014 and described in JRS as one of the "initiatives aimed at enhancing the competitiveness of companies" (JRS, 2013, p. 76). The index is based on such quantitative achievements as: three-years average ROE and operating profit, as well as market value (JPX-Nikkei Index 400 Guidebook, 2016). Major qualitative requirements are: an appointment of at least two independent outside directors, and an adoption of IFRS (International Financial Reporting Standards) (JPX-Nikkei Index 400 Guidebook, 2016).

Another influential actor that has advocated shareholders' rights is foreign investors, which shareholding proportion was 30.1 percent as of 2016 (TSE, 2017, p. 2; Figure 3). Japanese companies with higher levels of foreign stockholding are characterized by higher risk-taking propensity (Yoshikawa et al., 2005;[START_REF] Nakano | Effects of Accounting Conservatism on Corporate Investment Levels, Risk Taking, and Shareholder Value[END_REF] and downsizing in the attempts to maximize SV [START_REF] Ahmadjian | Safety in numbers: Downsizing and the deinstitutionalization of permanent employment in Japan[END_REF][START_REF] Ahmadjian | A clash of capitalisms: Foreign shareholders and corporate restructuring in 1990s Japan[END_REF]. Conversely, domestic ownership proportion [START_REF] Abe | Employment policy and corporate governance-An empirical comparison of the stakeholder and the profit-maximization model[END_REF]Yoshikawa et al., 2005) and ownership concentration [START_REF] Fiss | The diffusion of ideas over contested terrain: The (non) adoption of a shareholder value orientation among German firms[END_REF][START_REF] Witt | Varieties of Capitalism and institutional comparative advantage: A test and reinterpretation[END_REF] are associated with strategic rather than financial interests.

H2. Foreign shareholding is positively related with proportions of nonregular employees.

The previous literature accounts for organizational size, age, reputation, wages, foreign ownership [START_REF] Ahmadjian | Safety in numbers: Downsizing and the deinstitutionalization of permanent employment in Japan[END_REF] and board size [START_REF] Abe | Employment policy and corporate governance-An empirical comparison of the stakeholder and the profit-maximization model[END_REF] as key determinants of corporate legitimacy in the Japanese context. This research comes up with another proxy, which is the inclusion into Nikkei Index 400. It is referred to as "shame index" for its utmost reputational importance for large companies (Patrick, 2015, p. 16). The presented evidence about the importance of reputational assets for Japanese listed companies being relevant, requires an important clarification. A key economic reason for implementing the CG reforms agenda has been the shrinking domestic market that has induced companies to search for export-oriented strategies [START_REF] Milhaupt | Evaluating Abe's Third Arrow: How Significant are Japan's Recent Corporate Governance Reforms?[END_REF]. In other words, internationalization has been regarded as a means for sustainable corporate growth. In order to attract more investment and be able to expand globally, companies need to adhere to recognized accounting and CG standards. However, not all the firms have succeeded to internationalize. With the weakening of business-finance nexus in early 1980s, large multinational companies (MNCs) became less dependent on a national industrial policy, which allowed them "to allocate resources based on corporate strategy mainly oriented to maximize [their] position in global value chains" (Lechevalier et al., 2016, p. 25). This has helped them to alleviate the consequences of the 1990s' bubble burst [START_REF] Yamada | The Theory of Regulation in Times of Crises -International Conference Research & Regulation[END_REF]. On the contrary, internally-focused companies have been much more dependent on partner banks and less capable of issuing equity, which would potentially improve their accounts. Hence, while MNCs have been increasing their internal reserves by issuing stock and investing overseas, domestic-oriented companies have been mostly concerned CEAFJP DISCUSSION paper series #18-01 with repaying debts, which made their growth almost negligible -much in line with minimal growth of Japan's GDP during the last three decades.

In their similar study, Yoshikawa et al. (2005) used return on assets (ROA) as a moderating variable reflecting firms' performance. Other moderating variables include R&D intensity and the "degree of internationalization" (DOI). Existent scholarship links higher degrees of R&D intensity to lower financial pressure (Gospel & Pendelton, 2003). In other words, managers whom creditors offer longer pay-back periods, enjoy more freedom of investing into long-term projects, including various forms of human resource development. Thus, R&D intensity is negatively correlated with employment downsizing [START_REF] Lechevalier | How did the Japanese Employment System Change? Investigating the Heterogeneity of Downsizing Practices across Firms[END_REF]. The proxy for DOI is FSTS (Foreign Sales as a Percentage of Total Sales), which is the most common method used in previous studies [START_REF] Sullivan | Measuring the degree of internationalization of a firm[END_REF]. DOI is regarded in the literature as a stimulation for labor downsizing due to pressures related to international competition [START_REF] Lechevalier | How did the Japanese Employment System Change? Investigating the Heterogeneity of Downsizing Practices across Firms[END_REF]. However, while more internationalized companies might resort to more frequent downsizing, it is not evident, whether they are likely to increasingly rely on nonregular workforce. Based on this consideration, I offer the following hypothesis: H3. DOI and R&D are negatively correlated with ratio of nonregular employment.

Panel Data Analysis

Sources: NEEDS FinancialQUEST database and annual securities reports of Nikkei Index 400 companies retrieved from kabupro.jp.

Selection criteria: Nikkei Index 400 is a political economic project outlined in Japan Revitalization Strategy as one of the "initiatives aimed at enhancing the competitiveness of companies" (Japan Revitalization Strategy, 2013, p. 76). The index consists mostly of large companies that are subject to internationalization and thereby decoupling from national economy. It supposedly: (1) encompasses interest of non-stable shareholders, management and core employees to the highest degree while (2) downplaying interests of nonregular employees.

Dependent variable: Proportion of nonregular employees

Independent variables:

-Shareholder value (SV) proxies:

-Tobin's Q (Q = Equity Market Value ÷ Equity Book Value) [START_REF] Nakano | Effects of Accounting Conservatism on Corporate Investment Levels, Risk Taking, and Shareholder Value[END_REF] -Total shareholder return (TSR = Share price at end of year -Share price at the beginning of the year + Dividends per share) ÷ Share price at beginning of year) [START_REF] Dobbs | Measuring stock market performance[END_REF] -Director ownership: shows the degree of alignment between directors and shareholder and, hence, the extent of directors' potential compliance with shareholders' clams to raise SV (Gospel & Pendelton, 2003) -Annual general meeting (AGM). Japan's AGMs are often held on a same day and within a short period of time. This measure was introduced to formalize meetings and limit outside shareholders' interference. Thus, I differentiate between companies that chose to hold AGM during the most popular day ("1"), indicating limited shareholders' influence, and the rest ("0"), more opened to shareholders' demands

Control variables:

-Ratio of Nonregulars t-1 . Since the changes in the proportion of nonregular employees are incremental, I include the dependent variable lagged by one year as a control variable -Degree of internationalization (DOI): exports ÷ net sales -R&D intensity: R&D expenses ÷ net sales

The analyzed panel data sample contains 245 firms belonging to the Nikkei Index 400 with data from 2010 till 2017. Each company's data encompasses the period between two and eight years, which makes the panel unbalanced. I excluded financial companies due to their different accounting standards. Because of the limited availability of information on nonregular employees in the NEEDS FinancialQUEST database, the starting year of analysis is 2010, the final year is 2017, which makes 1762 observations in total. I used R software (R Core Team, 2017) that includes various statistical packages to analyze and visualize data. The used packages are: "ggplot2" [START_REF] Wickham | ggplot2: Elegant Graphics for Data Analysis[END_REF], "lme4" [START_REF] Bates | Fitting Linear Mixed-Effects Models Using lme4[END_REF], "plm" [START_REF] Croissant | Panel data econometrics in R: The plm package[END_REF], "sjmisc" (Lüdecke, 2018), "sjPlot" (Lüdecke, 2018b) and "stargazer" [START_REF] Hlavac | What connects industrial relations and corporate governance? Explaining institutional complementarity[END_REF]. CEAFJP DISCUSSION paper series #18-01

Dependent variable: Ratio of Nonregulars

As seen from the Figure 4, companies belonging to the "Retail", "Real Estate" and "Food" industries have the highest median and average ratios of nonregulars, while "Electronics", "Machinery" and "Chemical" employ the lowest proportions of temporary employees. The same observation holds true for the yearly averages per industry, which CEAFJP DISCUSSION paper series #18-01 can be inferred from the Figure 5. Such distribution is logical, since companies with highest proportions of nonregular employees belong to labor-intensive industries, which means they can improve their balance sheets by decreasing average labor costs. On the other hand, companies belonging to capital-intensive industries have the lowest rates of temporary employees. Their profits are less dependent on human resources, and, hence, there is not much rationale to curb labor cost per employee.

The distribution of the dependent variable "Ratio of Nonregulars" is skewed to the right, as seen from the Figure 6. From this type of distribution, we can corroborate that the mean is larger than the median. The descriptive statistics table (Table 1) proves this. We can also infer from the density plot (Figure 6) that the distribution is bimodal (the third mode can be distinguished towards the right end of the distribution, but it is less evident). It can be corroborated from the Figure 7 that the distribution of nonregulars that closely resembles the general right-skewed bimodal pattern is observed for such industries as: Chemical, Electronics (which also has a third mode), Machinery and Services.

Regression

The F test showed a low p-value (< 2.2e-16), which counts against the null hypothesis that the "pooled OLS model" is adequate, in favor of the fixed effects alternative. The Breusch-Pagan test for unbalanced panels showed a low p-value (< 2.2e-16), which also counts against the null hypothesis that the "pooled OLS model" is adequate, in favor of the "random effects model" alternative. Finally, the Hausman test showed a low p-value (< 2.2e-16), which counts against the null hypothesis that the "random effects" model is consistent, in favor of the "fixed effects model". Although the "fixed effects model" appears the most appropriate for my data, to demonstrate the similarities/differences in these models and to improve the robustness of the analysis, I include all three of them into the comparative regression tables.

As for the "fixed effects model", I have run two regressions with the "individual" and "two-ways" effects respectively (both have the p-values < 0.01, meaning high levels of significance). While the "individual" effects assume the company-specific differences that are constant over time, the "two-ways" effects assume both "individual" and "time" effects. In other words, the "two-ways" effects imply that differences have been both time-sensitive and company-specific. It is likely that company-specific differences have been timeinvariant (since I look at a relatively short period of time, which is eight years), granting the entrenched nature of Japanese institutions and the resulting incremental change within the local corporate environment. However, it is also possible that changes occurred over time as well, as the proportion of nonregular employees has been increasing from 2010 to 2017.

The main regression model used in this research looks as follows:

where Nonregular it is the ratio of nonregular employees to total employees for the company i at time (year) t. γ i denotes industry-and firm-specific effects, while ε it stands for the residuals or the noise of the model.

Next, I considered applying the linear mixed model (LMM). I chose to test this model for two reasons. First, it is used when the response variable has a non-normal distribution. This holds true for the "Ratio of Nonregulars" dependent variable, which has right-skewed bimodal distribution, as shown above (Figure 6). Second, the LMM allows to account not only for fixed effects (company and industry) but also for random effects within each unit (company) occurring over time [START_REF] Mcculloch | An introduction to generalized linear mixed models[END_REF]. In other words, the LMM also captures non-independence that exists between time-observations (years 2010-2017) for each individual company. "The random variables of a mixed model add the assumption that observations within a level, the random variable groups, are correlated. Mixed models are designed to address this correlation and do not cause a violation of the independence of observations assumption from the underlying model, e.g. linear or generalized linear" (SSCC, 2016). When comparing R 2 of the fixed-effects and LMM models, the latter has a clear advantage (marginal R 2 of the LMM is 52 percent, which is almost two times higher than the R 2 of the fixed-effects). Moreover, the LMM has a smaller Akaike information criterion (AIC) estimation (-7,166.45) than the fixed-effects model (-4,489.661) which also confirms that the mixed-effects model has a better fit (Table 3).

I have conducted the t-test and applied the variance inflation factor (VIF) to make sure that there is no multicollinearity among the explanatory variables. Both procedures showed that there is no such a problem. The results of the t-test that computes pairwise correlations between explanatory variables can be seen from the Table 2.

Results and Discussion

The hypotheses listed in this paper look as follows:

1. Higher levels of SV are associated with higher proportions of nonregular employment.

2. Foreign shareholding is positively correlated with proportions of nonregular employees at Nikkei Index 400 firms.

3. DOI and R&D are negatively correlated with nonregular employment at Nikkei Index 400 companies. CEAFJP DISCUSSION paper series #18-01

The regression coefficients obtained through the application of the LMM model are shown on the Figure 8. Each coefficient demonstrates the change in the response variable (Ratio of Nonregulars) provided we control for other explanatory variables. Excluding the lagged dependent variable, ROA has a highest correlation coefficient with the response variable (0.06), while Productivity, AGM and Total Assets are the only variables with negative coefficients. Among them, only Productivity is significantly correlated with the Ratio of Nonregulars. On one hand, as seen from the Table 6, Tobin's Q, which is one of the proxies for shareholder value (SV), does not show significant correlation with the proportion of nonregulars. On the other hand, total shareholder return (TSR) -another SV proxyis positively (0.006) and significantly (at the 0.01 level) correlated with the proportion of nonregular employees. Since the TSR variable indicates stock market fluctuations and dividends per share, it is highly possible, based on the regression results, that higher stock prices and higher dividends are associated with downsizing and cutting of labor costs, primarily via the growing reliance on temporary employees.

Regarding the Hypothesis 2, thus far, the correlation between foreign ownership and nonregular employment is not significant. At the same time, foreign shareholding appears to be correlated with higher profitability measured as ROA (0.39, at the 0.01 significance level) and Tobin's Q (0.001, at the 0.01 significance level), but lower productivity (-0.0004, at the 0.01 significance level) (Table 7). This can be interpreted in a following way: increase in foreign shareholding is likely to be associated with higher corporate revenue, but not with higher efficiency of production. The positive correlation between foreign shareholding and profitability is also valid for linear correlation by industry, with the only exception of "Real Estate" (Figure 11).

While there is no significant correlation between foreign ownership and the ratio of nonregulars, such correlation is observed between domestic ownership and the ratio of nonregulars. These variables are positively (0.05) and strongly (at the 0.01 significance level) correlated. This result can be interpreted in a following way. The pertaining institutional compromise between finance, management and regular employees allows core workers to retain their traditional benefits, which comes at price of virtually zero remuneration growth. [START_REF] Ahmadjian | Safety in numbers: Downsizing and the deinstitutionalization of permanent employment in Japan[END_REF] and [START_REF] Ahmadjian | A clash of capitalisms: Foreign shareholders and corporate restructuring in 1990s Japan[END_REF] show that companies with higher levels of domestic shareholding are less prone to downsizing. In other words, domestic ownership is associated with stricter adherence to social guarantees for core employees. It also shows stronger managerial influence, since CEOs are protected by insider ownership from potential hostile takeovers (Gospel & Pendelton, 2003). Most of the large Japanese companies, regardless of their ownership structure, have tended to cut their labor costs during the last three decades to improve their competitiveness. Hence, if a company chooses not to downsize its regular workforce, the only way for it to curb average labor costs is to freeze the hiring of new regulars and to intensify the hiring of nonregulars [START_REF] Lechevalier | How did the Japanese Employment System Change? Investigating the Heterogeneity of Downsizing Practices across Firms[END_REF]. The data on degree of internationalization (DOI) and R&D intensity required to test the Hypothesis 3 is provided approximately by the half of the analyzed companies: 145 and 140 firms out of 245 disclosed the information regarding their R&D activity and exports respectively. It can be inferred from the Table 4 that DOI is negatively (-0.028) and significantly (at the 0.01 level) correlated with the Ratio of Nonregulars. This result is in line with the Hypothesis 3. It assumes that companies with higher proportions of overseas sales are the ones less likely to employ higher proportions of temporary employees. This can be due to higher extent of integration into global value chains, which leads to more vigilant supervision of labor standards by international investors. Since nonregular employment in Japan is associated with relatively inferior status and poor social benefits, more internationalized companies are likely to refrain from over-reliance on nonregulars.

As regards the R&D intensity, Table 6 shows negative (-0.188) and significant (at the 0.01 level) correlation between the R&D intensity and the Ratio of Nonregulars, which also confirms the Hypothesis 3. This coefficient can be interpreted in a following way. Firms that invest more in R&D are overwhelmingly capital-intensive. Hence, they depend less on human resources relatively to labor-intensive industries such as services, retail and food. Since capital-intensive firms have higher entry barrier for their workforce, it is relatively smaller, but, as a rule, composed of more qualified regular employees. On contrary, laborintensive companies invest less and hence, are less dependent on capital. In turn, their profits are associated with control over labor costs that can be curbed by increasing the proportion of nonregular employees.

The panel data analysis yielded some other valuable results. Firstly, ROA shows strong positive correlation with the proportion of nonregulars. It can be corroborated from the positive (0.078) and significant (at 0.01 level) correlation coefficient. The likely interpretation CEAFJP DISCUSSION paper series #18-01 of this correlation is that nonregular employees are instrumental for achieving higher levels of corporate profitability.

On the other hand, these higher profits are not earned in a sustainable way. As seen from the Table 6, productivity is negatively (-0.0004) and significantly (at 0.01 level) related to the proportion of nonregular employees, provided we control for other independent variables. The possible explanation is: the higher is the share of nonregulars at company, the less is the output per employee. This result confirms previous studies [START_REF] Jones | Income Inequality, Poverty and Social Spending in Japan[END_REF][START_REF] Aoyagi | Labor Market Reform: Vital to the Success of Abenomics[END_REF] that found out that employers are less eager to invest into training of flexible employees. This, in turn, leads to low working motivation among nonregulars as compared to core workers, which explains lower productivity rates for enterprises with higher proportions of nonregular workforce. It can also be inferred from the Figure 12 that the negative linear correlation between the Ratio of Nonregulars and Productivity holds true for all industries except "Communications" and "Electronics".

Conclusions

This paper has aimed to analyze the effects of the shareholder value pursuit on labor situation at large Japanese listed companies. While the similar studies have highlighted such effects as downsizing and decreased labor costs, this research is novel for its focus on the labor bifurcation, whereby the proportion of nonregular employees has drastically increased. I offer the political economic analysis of Japanese corporate institutions to substantiate the following finding. The increase in the proportion of nonregulars has been reinforced by the recently-formed political economic coalition.

On one hand, the coalition includes outside shareholders as vital providers of capital to Japanese joint-stock companies against the relative decline of debt finance. On the other hand, this political economic bloc insulates managers from direct shareholders' interference and preserves the entrenched alliance between managers and core employees. Thus, current corporate transformations in Japan pursue the strategy of killing two birds with one stone: enhancing the interests of shareholders while preserving institutional integrity.

My article demonstrates that this tactic comes at price of sacrificing the interests of labor. Among others, it is becoming increasingly composed of nonregulars who have minimal chances to become core employees. In a nutshell, the growing proportion of temporary workforce is associated with two factors: higher total shareholder return, which is one of the shareholder value proxies, and domestic ownership, which reflects managerial entrenchment.

Limitations

First, the presented panel data analysis on nonregular employees does not account for dispatch workers (haken). However, since their number is relatively small (six percent of nonregulars), this should not significantly affect the results of the research.

Second, I only analyze the constituencies of Nikkei Index 400, which are large companies. Hence, my findings might not be generalized for the SMEs as well as unlisted companies.

Third, while I only account for the stock market influence on labor bifurcation, the model is likely to be more accurately explained through the inclusion of capital market variables. For example, international competition certainly affects employers' decision on whether to hire more nonregular employees. Therefore, I do not claim that my independent variables solely explain the increase in temporary employment. In turn, I argue that the shareholder value pursuit is likely to intensify the labor bifurcation at Japanese joint-stock enterprises.

List of Figures and Tables

List of Figures and Tables

Figure 1 .

 1 Figure 1. Proportion of Regular and Nonregular Employees. Source: Labour Force Survey (2017)

Figure 2 .

 2 Figure 2. Types of Nonregular Employment. Source: Labour Force Survey (2017)

Figure 3 .

 3 Figure 3. Distribution Percent of Market Value Owned by Type of Shareholder. Source: Tokyo Stock Shareownership Survey (2017)

Figure 4 .

 4 Figure 4. Distribution of Nonregulars Across Industries

Figure 6 .

 6 Figure 6. Density Plot for the Ratio of Nonregulars

Figure 8 .

 8 Figure 8. Correlation Coefficients of the LMM

Figure 9 .

 9 Figure 9. Q-Q Plot for Random Effects

Figure 11 .

 11 Figure 11. Correlation Between Foreign Ownership and ROA Across Industries

Figure 12 .

 12 Figure 12. Correlation Between Proportion of Nonregulars and Productivity Across Industries

Figure

  Figure 1. Proportion of Regular and Nonregular Employees. Source: Labour Force Survey (2017) p. 5

5 Figure 2 .Figure 3 .Figure 7 .

 5237 Figure 1. Proportion of Regular and Nonregular Employees. Source: Labour Force Survey (2017) p. 5 Figure 2. Types of Nonregular Employment. Source: Labour Force Survey (2017) p. 6 Figure 3. Distribution Percent of Market Value Owned by Type of Shareholder. Source: Tokyo Stock Shareownership Survey (2017) p. 11 Figure 4. Distribution of Nonregulars Across Industries p. 14 Figure 5. Average Yearly Ratios of Nonregulars p. 14 Figure 6. Density Plot for the Ratio of Nonregulars p. 15 Figure 7. Density Plot for the Ratio of Nonregulars by Industry p. 15 Figure 8. Correlation Coefficients of the LMM p. 18 Figure 10. Slopes of Coefficients p. 19 Figure 11. Correlation Between Foreign Ownership and ROA Across Industries p. 20 Figure 12. Correlation Between Proportion of Nonregulars and Productivity Across Industries p. 22

Table 1 .

 1 Descriptive Statistics][

Table 2 .

 2 Correlation Matrix][

Table 3 .

 3 Panel data analysis for the constituencies of Nikkei Index 400][Table4. Panel data analysis for the constituencies of Nikkei Index 400 (including DOI and R&D Intensity)] [Table5. Panel Data Analysis for JPX-Nikkei Index 400 (Including DOI)] [Table6. Panel Data Analysis for JPX-Nikkei Index 400 (Including R&D Intensity)] [Table7. Panel Data Analysis for JPX-Nikkei Index 400 (Foreign Ownership)] 23 Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies

Table 1

 1

	. Descriptive Statistics

Table 3 .

 3 Panel data analysis for the constituencies of Nikkei Index 400 p. 26

Table 4 .

 4 Panel Data Analysis for JPX-Nikkei Index 400 (Including DOI and R&D Intensity) p. 27

Table 5 .

 5 Panel Data Analysis for JPX-Nikkei Index 400 (Including DOI) p. 28

Table 6 .

 6 Panel Data Analysis for JPX-Nikkei Index 400 (Including R&D Intensity) p. 29

Table 7 .

 7 Panel Data Analysis for JPX-Nikkei Index 400 (Foreign Ownership) p. 30

Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock Companies

Table 2. Correlation Matrix

CEAFJP DISCUSSION paper series #18-01Table 3. Panel data analysis for the constituencies of Nikkei Index 400 27 Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock CompaniesTable 4. Panel Data Analysis for JPX-Nikkei Index 400 (Including DOI and R&D Intensity)

CEAFJP DISCUSSION paper series #18-01Table 5. Panel Data Analysis for JPX-Nikkei Index 400 (Including DOI) 29 Impact of Shareholder-Value Pursuit on Labor Policies at Japanese Joint-Stock CompaniesTable 6. Panel Data Analysis for JPX-Nikkei Index 400 (Including R&D Intensity)

CEAFJP DISCUSSION paper series #18-01Table 7. Panel Data Analysis for JPX-Nikkei Index 400 (Foreign Ownership)

Acknowledgements

This paper was presented for the first time during the 2018 SASE Annual Conference that was held in June 2018 at Doshisha University. A revised version of this paper is to be published in The Japanese Political Economy. The author may be contacted at k.ovsiannikov@gmail.com.

Annexes