Because in many SMEs (Small and Medium-sized Enterprises), the amount of work largely fluctuates, it isdifficult to secure human resources in keeping with the changing environment. While in busy periods, workers may notfinish all the work, in idle periods, they may not have enough work to do. In order to adjust to the fluctuating workload,there are various employment methods such as temporary staff services and outsourcing workforce and services. However,it is very important to make effective use of regular employees. The aim of this paper is to level out the working hours ofworkers and introduce a new inter-company P2P (Peer to Peer) human-resource sharing platform where companies duringtheir idle periods can offer their employees to companies in their busy periods using an automated negotiation technology.The effectiveness of this new platform will be evaluated and verified using multi-agent simulation.

Pedestrian traffic is reported to be a component of rental price. However, rental price analysiswith an agent-based simulation has not been conducted. In this article, shop rental around Shimokitazawastation is analyzed by conducting an agent-based simulation. The result shows that there is a positivecorrelation between shop rental and the number of footprint, which is the output of the agent-basedsimulation.

駐輪ステーション間を自由に往来できるシェアサイクル事業の運営では、自転車の偏在による機会損失を解消するため、トラックによる再配車を行なっている。本研究では、変動型インセンティブを提示することにより、自転車の偏在を解消し、従来のシェアサイクル事業の運営とは抜本的に異なる運営方法の検証を目的とする。検証には、オフィス街利用・観光地用の2つのシナリオを想定し、利用者と駐輪ステーションをエージェントとするマルチエージェント・シミュレーションを用いる。各シナリオにおいては異なるエージェントモデルを作成し、駐輪ステーションエージェントには、自律的な学習による有効な方策を確認するため、強化学習を利用する。

This paper proposes a method of building a polarity dictionary using news articles and stockprices in the Chinese market by textual analysis in finance. In order to measure the degree of polarity, weassociated the news articles' sparse composite document vectors to a score. The score is calculated by themethod of event study with the abnormal change rate of stock prices on the publication date. Weconducted support vector regression (SVR) and built a polarity dictionary with polarity data from learners.Furthermore, we made a comparison on accuracy to traditional ways of calculating word polarity inwhich news articles are represented by a one-hot wordlist. The comparison of the existed polarity is made.

There are many types of goods in retail stores such as supermarkets. While the goods positionmay be changed by store staffs, management of goods position may be insufficient. In this study, weproposed a model for estimating goods position in retail stores through association analysis and analyzingthe staying time of customers in divided areas in the store, using customer's purchase history and movementhistory of customers. In this paper, we show some results from our experiments and point out several futureworks.

本研究は、外食産業の POS データを用いて経営力向上に繋げるサービスの実現を目的としている。日本の外食産業は、労働生産性が低い上、慢性的な人手不足で人材確保に苦労している。そこで、この課題を解消する対策として、1 テーブルごとの客単価向上が有効と仮説を立て、客単価の高い高級焼肉店の POS データを分析した。顧客の購買行動の特徴を明らかにし、機械学習を用いてフィンテック応用を含めた販売政策の検討を行う。

To keep up with rapid changes in the business environment, Japanese companies have requiredto conduct business transformation in recent years. In this paper, we classified companies by using FuzzyC Means, and estimated the synergy effect of multi-business companies based on that classification. Inaddition to this, we investigated the corporate behavior, especially when making a decision to sell a business,focusing on divestment through M&A.

Merger and Acquisition (M&A) has become more and more popular these days. While M&A is aneffective strategy, it also has a big risk for companies. According to the study in U.S., over 60% of M&Aended in decreasing the shareholder value. What is worse,even though M&A is one of the biggest bet for thecompanies, we still don't have the clear answer for the reason of those failures. The previous studies aremostly based on comparing success cases and failure ones. However, since M&A is a dynamic activity andinvolves many stakeholders, surveying the past cases may not be enough and we need the way to simulatethis dynamics. Thus, in this paper, we would like to emulate M&A activity as gaming and aim to find theinsights on success / failure factor of M&A.

Company executives play an important role in corporate activities. In this research, we focus onthe characteristics of the top executive, who make the important decisions. We attempt to measure the facialemotional score of these executives from the photographs published on their firm's annual report. Inaddition, we create a narcissism index from the number of times these executives appear on their reports.Finally, we analyze how these emotional scores or narcissism indexes relate with their company'sperformance and behavior.

近年，上場会社の不適切な会計処理が問題とされる事例が増加する傾向にあり，その一方で，監査を担当する監査法人の業務は人的制約や時間的制約等により，十分なリソースを投入することが難しい状況になっている．このような状況に対応するために，現在は監査人が個人の経験や資質と各監査法人のマニュアルに基づいて行っている監査リスク（監査人が財務諸表の重要な虚偽の表示を看過して，誤った意見を形成する可能性）の評価に対して，財務情報，統計情報等を使用する財務分析，統計分析に機械学習による異常検知や異常値判別，時系列分析等の手法を加えた新たな監査リスクの分析手法を検討する．

Research on the association between stock price fluctuations and news data is popular andnumerous studies have been conducted. This paper aims to improve the accuracy of text classification intothree categories (negative, neutral, or positive) by employing high frequency data and LSTM model. Oneof the novelties of our paper is to use several types of news articles in the analysis.

News reports can be one of the main factors that influence commodity futures prices. In thispaper, we conducted analysis on the relationship between news reports and commodity futures. Firstly, wedeveloped a fluctuation index of the futures prices on a daily basis, through event study. Next wevectorized the news report data and analyzed their relationships with the futures prices. In this analysis,we used the multivariate autoregressive model to examine the possibilities of forecasting commodityfutures prices by using the news report index. We also analyzed the relationship between the news indexdeveloped in this paper and the stock prices of enterprises related with commodity futures.