• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.135-140
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• 2004

It considers advertising as an instrument to increase the stock of goodwill or reputation. summarising the effects of past and current advertising expenditures carried out by a firm. on the current demand for her goods. A relevant result emerging from the Dorfman-Steiner (1954) condition. establishing that advertising investment is proportional to sales. This paper investigates optimal advertising level between the good firm and the bad firm. So. We knew that between the good firm and the bad firm are establishing the Dorfman-Steiner condition.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.1-17
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• 2024

One of the most important decisions for managers in the online banner advertising industry, is to choose the best banner alternative for exposure to customers. Since it is difficult to know the click probability of each banner alternative in advance, managers must experiment with multiple alternatives, estimate the click probability of each alternative based on customer clicks, and find the optimal alternative. In this reinforcement learning process, the main decision problem is to find the optimal balance between the level of exploitation strategy that utilizes the accumulated estimated click probability information and exploration strategy that tries new alternatives to find potentially better options. In this study we analyze the impact of word-of-mouth effects and the number of alternatives on the optimal exploration-exploitation strategies. More specifically, we focus on the word-of-mouth effect, where the click-through rate of the banner increases as customers promote the related product to those around them after clicking the exposed banner, and add it to the overall reinforcement learning process. We analyze our problem by employing the Multi-Armed Bandit model, and the analysis results show that the larger the word-of-mouth effect and the fewer the number of banner alternatives, the higher the optimal exploration level of advertising reinforcement learning. We find that as the probability of customers clicking on the banner increases due to the word-of-mouth effect, the value of the previously accumulated estimated click-through rate knowledge decreases, and therefore the value of exploring new alternatives increases. Additionally, when the number of advertising alternatives is small, a larger increase in the optimal exploration level was observed as the magnitude of the word-of-mouth effect increased. This study provides meaningful academic and managerial implications at a time when online word-of-mouth and its impact on society and business is becoming more important.

• Journal of the Korea Society for Simulation
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• v.13 no.1
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• pp.41-50
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• 2004

The purpose of this paper is to analyse the manager's policy to maximize the profit in a multiple-server queueing facility with a limited queue capacity. We assume that the level of advertizing effects on the arrival rate of customers to the facility. The model without ‘word of mouth effect’ is assumed that the arrival rate is independent on the qualify of service level. We estimate the service quality by the balking rate of customers from system. We extend this to the model with ‘word of mouth effect’. To achieve the maximum profit, the most important factor is the considerably high utilization of facility for both models. Given service rate, we should maintain an effective arrival rate to some extent. To this end, among the available options, an increase of advertizing effort is more desirable than reducing the fee if the service value of customers remains unchanged. We also investigate whether the variability of service time has a significant impact on determining the optimal policy. The cost of service variability is not so expensive as that in a single server model due to the reduced variability of service times in a multiple-server model.

• Asia pacific journal of information systems
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• v.23 no.2
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• pp.67-86
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• 2013

This study first provides a stylized model that captures the essential features of the SC (Social Commerce) business and the competition process. The model focuses on the relationship between key decision issues such as marketing inputs and market value. As more SCs join the industry, they are inevitably faced with fierce competition, which may lead to sharp increase in the total marketing and advertising expenditure. This type of competition may lead the industry away from its optimal development path, and at worst, toward a disruption of the entire industry ecosystem. Such being the case, another goal of this study is to examine the possibility that the ToC (Tragedy of the Commons) may occur in the SC industry. We build game models, each of which assumes homogeneity and heterogeneity of SC providers, respectively, and derive explicit equilibrium solutions from both models. Our basic analysis presents Nash equilibria in both models and shows that SC providers are inevitably faced with fierce competition, which may lead to sharp increase in the total marketing expenses. We also compare the game outcomes with one with a hypothetical social planner who determines the total marketing level that optimizes the entire market value. Then, ToC can be defined to describe the situation where the total marketing efforts exceed the socially optimal level of marketing efforts. In both models, we examine the possibility of the ecosystem disruption and specify the conditions under which ToC may occur. However, the chance of avoiding ToC is higher with heterogeneous players than with homogeneous players. To supplement our analytical results, we develop a simulation model which incorporates a market dynamics based on the gap between actual marketing efforts and socially optimal marketing level. Simulation experiments present some lessons and insights which also confirm out findings from equilibrium analysis. For example, heterogeneity in SC providers alleviates the severity of ToC and makes it faster for survivors to escape from the ToC trap. As a result, the degree of industrial concentration tends to increase, which also explains the 'rich-get-richer' phenomenon observed in some empirical studies on the SC industry. Lastly, based on our analytical and experimental results, we come up with some measures to avoid ToC and overcome the shortcomings intrinsic to the current business model. And further discussions provide strategic implications and policy directions to overcome the possible trap of ToC in this ecosystem, and eventually help the industry to sustainably develop itself toward the next level. To name a few examples of policy measures, regulations on the marketing activities so that the overall marketing expenses cannot go beyond the socially optimal level; institutional guidelines and rules to straightening up the distortions in the way that SC providers view the marketing costs (the current marketing costs are underestimated, thereby encouraging SC providers to increase marketing expenditure); and so on.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.444-453
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• 2018

The study addresses the analysis on the financial determinants of corporate research and development (R&D) expenditure in finance. Overall level of R&D spending was estimated as one of the top-tier on a global basis and a majority of the expenditure was invested by large domestic firms in private sector. Consequently, financial factors that influence R&D intensity were empirically tested in the first hypothesis by using conditional quantile regression model for firms listed in KOSPI stock market in the post-era of the global financial turmoil. Firms in the groups of high- and low-R&D intensity were statistically compared to detect financial differences in the second hypothesis which was accompanied by the test of multi-logit model that included firms without R&D outlay. Concerning the results of the hypothesis tests, R&D spending of the prior fiscal year, firm size, business risk and advertising expense overall showed statistically significant impacts to determine the level. As an extended study of [1] that had examined financial factors of R&D intensity at the macro-level, the results of the present study are anticipated to contribute to maximizing shareholders' wealth in advance or emerging capital markets, when applied to find an optimal level of R&D expenditure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.446-453
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• 2018

The study examines corporate research & development (R&D) expenditure in modern finance. Firms may face one of the essential issues to maintain their optimal levels of R&D expenditures in order to increase corporate profit. Accordingly, financial determinants that may influence R&D spending are statistically tested for firms listed on the KOSPI stock market during the period from 2010 to 2015. Financial determinants which may discriminate between firms in high-growth and low-growth industries are examined on a relative basis. Explanatory variables including one-period lagged R&D expenses (Lag_RD), cross-product term between the Lag_RD and type of industry (as a dummy variable), and advertising expenses (ADVERTISE) significantly influenced corporate R&D intensity. Moreover, high-growth firms in domestic capital markets showed higher Lag_RD, profitability (PROF) and foreign equity ownership (FOS) than their counterparts in low-growth sectors, whereas low-growth firms had higher market-value based leverage (MLEVER) and ADVERTISE. Overall, these results are expected to influence decision-making of firms concerning the optimal level of R&D expenditure, which may in turn enhance shareholder wealth.