• 期刊

Optimal Decisions of a Mass Customization Supply Chain under Customized Demand

We investigate a supply chain selling a mass customization (MC) product to the market. A decision model is built when the degree of customization, price and lead time of the MC product affect market demand. The optimal decisions of the MC supply chain are analyzed in non-cooperative decision-making and cooperative decision-making. Moreover, the sensitivity analysis of optimal customer order decoupling point (CODP) position is conducted. Our results show that compared with non-cooperative decision-making, the optimal CODP moves to a later position in cooperative decision-making. The relationships between the optimal CODP position and the price sensitivity coefficient are different in two different scenarios. The impact of the customization sensitivity coefficient on the optimal CODP position is opposite to the impact of the lead time sensitivity coefficient on the optimal CODP position. When the production cost coefficient or investment coefficient increases, the optimal CODP moves to an earlier position.

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Profanity and Hate Speech Detection

Profanity, often found in today's online social media, has been used to detect online hate speech. The aims of this study were to investigate the profanity usage on Twitter by different groups of users, and to quantify the effectiveness of using profanity in detecting hate speech. Tweets from three English-speaking countries, Australia, Malaysia, and the United States, were collected for data analysis. Statistical hypothesis tests were performed to justify the difference of profanity usage among the three countries, and a probability estimation procedure was formulated based on Bayes theorem to quantify the effectiveness of profanity- based methods in hate speech detection. Three deep learning methods, long short-term memory (LSTM), bidirectional LSTM (BLSTM), and bidirectional encoder representations from transformers (BERT) are further used to evaluate the effect of profanity screening on building classification model. Our experimental results show that the effectiveness of using profanity in detecting hate speech is questionable. Nevertheless, the results also show that for Australia tweets, where profanity is more associated with hatred, profanity-based methods in hate speech detection could be effective and profanity screening can address the class imbalance issue in hate speech detection. This is evidenced by the performances of using deep learning methods on the profanity screened data of Australia data, which achieved a classification f1-score of 0.84.

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Omni-channel Pricing and Procurement Strategies with Consumer Returns and Order Cancellation under Reference Point Effects

This paper considers the online retailer's omni-channel retail operations under reference point effects in which consumers can cancel their orders before payment and return the products after payment if the products doesn't meet their expectation. The online retailer's optimal pricing and inventory decisions are derived under the omni-channel strategy by maximizing the total expected utility. The analysis reveals a threshold strategy on the retailer's optimal pricing and inventory decisions and the optimal total expected utility while considering the impact of reference point effects. Moreover, with the increase of the retailer's loss aversion or the optimism level, the order quantity and overall expected utility decrease, while the optimal price presents a threshold type. Finally, the comparison of the utility performance between with and without reference point effects is presented.

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The Effect of Leverage on Investment, Dividends, and Company Value on The Real Estate Industry in Indonesia

The purpose of this study is to examine and explain the effect of leverage on the value of real estate companies listed on the Stock Exchange in Indonesia, with investment and dividend as mediators. The population in this study is all real estate companies listed on the Indonesia Stock Exchange. The total population was as many as 44 companies. The analytical method used is Generalized Structural Component Analysis (GSCA). The results of this study indicate that high dividend payments will cause decrease in value of company. Intense competition in real estate sector, companies to survive in industry must have product innovations. Consequence of dividend payments is that companies will use high amounts of leverage. Empirically, previous research examining the interaction between leverage, investment, dividends, and company value has produced inconsistencies in research results (gaps). This research focuses on the real estate industry in Indonesia.

• 期刊

Reassessing the Economic Scale and the Impacts of Tax Relief on an Emerging Industry in Taiwan

This study is to reveal the development roles of the sports industry in Taiwan and to reassess the gross domestic sport product by using the input-output table from the Directorate General of Budget, Accounting and Statistics and the Industry and Service Census data. The computable general equilibrium model is also introduced to simulate and then to explore the economic effects of tax relief for sports manufacturing and sports services industries. The results indicate that if the government expects to facilitate the development of the whole industry and enhance the overall economic effect through tax relief in the sports industry, the sports industry policy can be gradually oriented to encourage private investment in the sports industry and stimulate the non-governmental consumption tendency of sports services, rather than taking government expenditure as the main support for the development of sports services. The findings would provide the direction of policy recommendations for the sports industry and further serve as a reference when the government discusses and formulates policies for fostering the sports industry in the future.