Information Contents in Japanese OTC Drug Advertising from Elaboration Likelihood Model Perspective: Content Analysis of TV Commercials and OTC Drug Websites

Based on the Elaboration Likelihood Model, the current study investigates information types that are cross-promoted in Japanese pharmaceutical advertising. The results from a quantitative content analysis of OTC drug brands' TV commercials broadcasted in Japan between 2014 and 2015 and their corresponding product websites (n = 150) show that Japanese OTC drug promotions feature more informational cues in the latter; cues such as price, safety, quality, components, and guarantees/warranties are particularly prominent. Furthermore, product websites tend to focus more on rational appeals, whereas TV commercials emphasize emotional appeals. No difference is found between these media types regarding celebrity and noncelebrity endorser usage.     

Sustainable airline strategy using portfolio theory: A case study of remote islands in Japan

The thin and fluctuated market generally characterizing air transport to remote islands involves greater business risks for airlines. But air transport often plays an important role in the life and economy of such islands. This paper applies portfolio theory to explore how it can reduce business risks to air transport in this context. The concept of Tourism β is introduced to represent the risk associated with each island market relative to overall tourist demand in the region looking as at 31 airports on remote islands in Japan. The results showed that a well-diversified portfolio of multiple remote islands could reduce the score commercial risks for carriers.     

Electronic Marketing Communications: An Evolving Environment,but Similar Story Regarding the Perception of Unsolicited Commercial E-Mail and Postal Direct Mail

The internet is still a relatively new mass communication tool for advertisers and marketers. When weighing the potential benefits of electronic techniques against the financial investment, spam seems particularly attractive to marketers for either for-profit or non-profit objectives. Since it is unlikely that marketers will decrease their efforts related to spam and postal direct mail as a form of communicating to mass consumers, it is important to track consumer attitudes so that audiences are not subjected to the backlash predicted by psychological reactance. The results of this study found that spam is more irritating than postal direct mail at both T₁ (2004) and T₂ (2006), and participants in T₂ found both direct marketing communication methods more intrusive than those in T₁.     

Two Types of Disagreement in Group Discussions of Japanese Undergraduates

In this study we investigated the nature of disagreement, which is a necessary component of a good discussion. We obtained 27 group discussion scenes by Japanese undergraduates that were evaluated by two ways: impression rating and ranking. As a result of factor analysis for the impression rating data, five factors were extracted: activeness, multidirection and unification of discussion, relationships of participants, development and sophistication of discussion, and sincerity of the participants, and each factor scores of each scene was simultaneously calculated. Each scene’s rank score was also calculated by relative comparisons. A significant positive correlation was found between the mean factor and the rank scores except for Factor 3 (relationships of participants). To consider the reason for the difference relating to Factor 3’s score, we scrutinized the discussion process of four scenes of the different patterns of the factor and rank scores. From the analysis of conversations, we suggested that this difference reflected ways of disagreement. By introducing a probative discourse tags for discussion (pDTD), we reasoned that the frequency of disagreement made Factor 3’s score negative and the absence of the second part of adjacency pairs made the rank score worse. The explicit speech and actions of blame such as emotional and aggressive expression, and neglect of treatment for the minor opinion made also the discussion unfair, but we think that these behaviors might erupt from the ground made by the accumulated implicit behaviors such as the absence of the second part. We finally concluded that the criticism type of disagreement increased the rank scores, and its censure type produced lower results, and the proper ways of disagreement in group discussions were discussed.     

The Influence of Acculturation and In-Group Bias on Source Credibility: The Case of Asian American Female Consumers

While research on cultural variables influencing source credibility has been called for by scholars, very few studies have made attempts thus far. In this study, an experiment was conducted to investigate the effects of acculturation and in-group bias on Asian Americans’ perceived source credibility and advertising effectiveness. The results indicate that while acculturation had some effects on the subcomponents of credibility, in-group bias did not have an effect on credibility and Asian Americans’ advertising responses.     

Estimating the benefits of effectively and proactively maintaining infrastructure with the innovative Smart Infrastructure sensor system

An innovative sensor system, designated ‘Smart Infrastructure,’ is being developed jointly by Cambridge University in the United Kingdom and Massachusetts Institute of Technology in the United States. This system provides real-time wireless information about the state of critical infrastructure. The Smart Infrastructure sensors are designed to monitor infrastructure, such as water pipelines, as well as to increase their capabilities for purposes of efficient maintenance. This paper presents a forecasting model that assesses the possible impacts of Smart Infrastructure technology currently being applied to the British water pipe market. In doing so, we identify key benefits of proactively managing infrastructure with such new technology. A probabilistic cost benefit analysis, which takes into account future uncertainty, is conducted using a Monte Carlo simulation. Our findings suggest that if the Smart Infrastructure sensor system is applied to water pipelines in the British market, there are likely to be significant economic benefits. They could be realised by avoiding disruption and damage costs (including water loss) due to water pipe bursts, as well as by reducing annual operating and maintenance costs. The mean cumulative net present value of savings derived from the case scenario for the period through year 2056 was estimated at US$ 23.7 billion.     

Algebraic structure of vector fields in financial diffusion models and its applications

High-order discretization schemes of SDEs using free Lie algebra-valued random variables are introduced by Kusuoka [Adv. Math. Econ., 2004, 5, 69–83], [Adv. Math. Econ., 2013, 17, 71–120], Lyons–Victoir [Proc. R. Soc. Lond. Ser. A Math. Phys. Sci., 2004, 460, 169–198], Ninomiya–Victoir [Appl. Math. Finance, 2008, 15, 107–121] and Ninomiya–Ninomiya [Finance Stochast., 2009, 13, 415–443]. These schemes are called KLNV methods. They involve solving the flows of vector fields associated with SDEs and it is usually done by numerical methods. The authors have found a special Lie algebraic structure on the vector fields in the major financial diffusion models. Using this structure, we can solve the flows associated with vector fields analytically and efficiently. Numerical examples show that our method reduces the computation time drastically.     

How Do Ordinary Japanese Reach Consensus in Group Decision Making?: Identifying and Analyzing “Naïve Negotiation”

The purpose of this study is to investigate ways in which ordinary Japanese people negotiate in a multi-party meeting. We initially gave such a way of negotiation the tentative name of “naïve negotiation”. The analysis of the conversational data reveals three structural features of naïve negotiation: (1) at the utterance level, the participants tend to claim their opinions without providing any overt grounds, (2) at the local consensus-building level, they tend to jump to conclusions without the full examination of proposed hypotheses, (3) at the final consensus-making level, there tends to be disjunctions between discussion units. Although these features are not necessarily seen as irrational or illogical, a naïve-negotiation style can still be a trouble-source in achieving successful consensus-making. This leads us to emphasize the necessity of developing a support system for the discussants.     

On Pricing Exponential Square Root Barrier Knockout European Options

A barrier option is one of the most popular exotic options which is designedto give a protection against unexpected wild fluctuation of stock prices.Protection is given to both the writer and holder of such an option.Kunitomo and Ikeda (1992) analytically obtained a pricing formula forexponential double barrier knockout options. Since the logarithm of theirproposed barriers for the stock price process S(t), whichisassumed to be geometric Brownian motion, are nothing but straight lineboundaries, the protection provided by them is not uniform over time. Toremedy this problem, we propose square root curved boundaries±btfor the underlying Brownian motion process W(t). Since thestandarddeviation of Brownian motion is proportional to t, theseboundaries(after transformation) can be made to provide more uniform protectionthroughout the life time of the option. We will apply asymptoticexpansions of certain conditional probabilities obtained by Morimoto (1999)to approximate pricing formulae for exponential square root double barrierknockout European call options. These formulae allow us to computenumerical values in a very short time (t < 10^–6sec), whereas it takesmuch longer to perform Monte Carlo simulations to determine optionpremiums.     

Forecasting Financial Market Volatility Using a Dynamic Topic Model

This study employs big data and text data mining techniques to forecast financial market volatility. We incorporate financial information from online news sources into time series volatility models. We categorize a topic for each news article using time stamps and analyze the chronological evolution of the topic in the set of articles using a dynamic topic model. After calculating a topic score, we develop time series models that incorporate the score to estimate and forecast realized volatility. The results of our empirical analysis suggest that the proposed models can contribute to improving forecasting accuracy.