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Marketers make an effort to affect consumers through scarcity marketing thus shaping the perception of scarcity and creating desirability for consumers. To expand the scarcity-expensiveness-desirability model and to enhance insights for practical applications, this study modifies the causal relationship among two types of scarcity, three types of expansiveness and desirability.

This study surveyed 400 Taipei city residents who had purchase experience with luxury brands products in Taiwan. The study employed structural equation modeling as empirical analysis.

The empirical results show that limited-quantity scarcity main influences perceived social status and then affects desirability. The second path is that limited-quantity scarcity influences perceived uniqueness and then affects desirability. Therefore, perceived social status and perceived uniqueness dominate the majority of effects on desirability because they are the recognition of the individual compared to others, especially when applied to luxury goods.

Because limited-quantity scarcity has a greater impact on desirability than limited-time scarcity in the empirical results, marketers can adopt limited-quantity scarcity messages that are better than limited-time scarcity, to increase consumers’ desire to purchase luxury goods.

The first novelty of this study is dividing scarcity marketing into limited-quantity and limited-time scarcity in the scarcity-expensiveness-desirability model. This study extends expensiveness in the scarcity-expensiveness-desirability model with a complete demonstration, that is, perceived social status, perceived uniqueness and perceived value, which is the second novelty of this study.

The Communist revolution in China has led to the appearance in this country of increasing numbers of Chinese books in Russian translation. The Chinese names in Cyrillic transcription have presented many librarians and students with a new problem, that of identifying the Cyrillic form of a name with the customary Wade‐Giles transcription. The average cataloguer, the first to meet the problem, has two obvious lines of action, and neither is satisfactory. He can save up the names until he has a chance to consult an expert in Chinese. Apart altogether from the delay, the expert, confronted with a few isolated names, might simply reply that he could do nothing without the Chinese characters, and it is only rarely that Soviet books supply them. Alternatively, he can transliterate the Cyrillic letters according to the system in use in his library and leave the matter there for fear of making bad worse. As long as the writers are not well known, he may feel only faintly uneasy; but the appearance of Chzhou Ėn‐lai (or Čžou En‐laj) upsets his equanimity. Obviously this must be entered under Chou; and we must have Mao Tse‐tung and not Mao Tsze‐dun, Ch'en Po‐ta and not Chėn' Bo‐da. But what happens when we have another . . . We can hardly write Ch'en unless we know how to represent the remaining elements in the name; yet we are loth to write Ch'en in one name and Chėn' in another.

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

The purpose of this paper is to research the impact of firms’ political connections on the stock price crash risk.

Empirical methodology is used in this study.

Using a large sample of Chinese firms for the period 2008-2013, the authors find that corporate political connections can reduce the stock price crash risk. When managers are still in politics or firms are in high financial transparency of local governments, the relationship between political connections and the stock price crash risk is weakened. In addition, the authors’ research shows that the corporate political connections influence the stock price crash risk by affecting the speed of confirmation of bad news.

The findings in this study suggest that political connections will affect corporate disclosure.

These results can help senior executives and investors make better decisions to prevent the stock price crash risk.

This paper empirically analyzes the impact of different types of political connections on the stock price crash risk for the first time.