Collaborative apparel consumption in the digital sharing economy: An agenda for academic inquiry

While apparel businesses leveraging the sharing economy have begun to emerge in recent years, academic research on “sharing” consumption for apparel is extremely limited. To fill this research gap, the researchers analyze current literature to present a conceptual framework that offers a durable theoretical foundation about the concept of collaborative consumption for apparel. Using a metatheory approach, the researchers develop a framework that explores how two major Internet‐supported collaborative consumption modes (utility‐based nonownership and redistributed ownership) manifest in an apparel context. Next, the researchers explore the implications of each consumption mode to understand the consumer's relationship with the product, peers, and businesses involved in these sharing schemes. A series of research propositions are also developed to stimulate discussion and future research about collaborative apparel consumption.     

Environmental Multi‐dimensionality and Staff Localization in Multinational Enterprises: The Case of Korean Firms

The person–environment fit theory posits that the term “environment” can be defined at different levels. This study delineates two environmental dimensions (strategic and organizational) and empirically examines the potential moderating effects of two strategic factors (intra‐ and inter‐regional diversification) on the relationship between two organizational factors (subsidiary ownership and host‐country experience) and MNE subsidiary staffing composition. The results indicate that strategic and organizational dimensions have impacts on subsidiary staffing composition. This study also finds that the interaction effects between strategic and organizational factors are significant only when there is congruence between demands from different environmental dimensions.     

A division of the capitalist class and the market for money capital

In a one‐commodity economy populated by capitalists equipped with equal endowment but with heterogeneous linear production technology, a division of the capitalist class emerges endogenously. The capitalists with relatively weak technology, yielding the profit rate lower than the interest rate, become a money capitalist (lender), whereas the capitalists with relatively strong technology, yielding the profit rate greater than the interest rate, become an industrial capitalist (borrower). The equilibrium interest rate is derived by the associated demand and supply relation. From this setup of the model follow two essential relationships Marx establishes between the average profit rate and the interest rate: (a) that the profit (rate) sets a maximum limit of interest (rate), and (b) that the two rates are correlated in the long‐run. Lastly, the profit rate of financial sector is less than that of industrial sector due to the basic setup of the model where the industrial sector uses leverage to amplify the underlying capital profit rate, whereas the financial sector lacks intermediation technology, which would have enabled it to borrow profitably.     

Leveraging ideas from user innovation communities: using text‐mining and case‐based reasoning

User innovation communities, where end users voluntarily share their ideas about new products or services, have become an important source of innovation. While efforts have been made to extract and develop ideas from these sources, existing studies have largely focused on company‐led efforts to facilitate user participation, rather than on voluntary user discussions within communities themselves. As a remedy, this research proposes to directly target those voluntary ideas from user innovation communities for product/service innovation. Because quantities of textual information within these communities are rather massive, we propose a modified and integrated approach of text‐mining (TM) and case‐based reasoning (CBR). Specifically, by constructing two casebases on ideas and existing products using TM and checking for overlap between the two using CBR, the approach enables the identification of opportunities for innovation and reference products for adaptation. We demonstrate the approach through a case of mobile apps in Apple App Store, and our findings suggest that the approach can help firms and users/developers broaden the source of ideas and leverage them into new product concepts.     

Application of social media analytics in tourism crisis communication

Given the newly established communication environment of social media and highly unpredictable crisis situations, this study questioned how tourists facing an unexpected crisis situation use social media to communicate and search for information. To this end, this study developed a multi-phased social media analytic framework (data crawling, data processing and text mining, social network analysis, semantic network analysis, and network visualization) to assess the structure of information exchanges between the members of a tourism organization’s social network community and identified influential actors and information content within the social network. This study’s findings suggest genuine ways of relating with and utilizing opinion leaders and influencers in social media marketing communication as well as crisis communication. The authors expect this proposed methodological framework of social media analytics to help other scholars scientifically identify and implement the proper methodologies for utilizing social media data.     

The price of going green: the role of greenness in green bond markets

In this paper, we empirically investigate how greenness information is priced in the green bond market. Our comparison of liquidity-adjusted yield premiums of green bonds versus synthetic conventional bonds indicates that, on average, there is no robust and significant yield premium or discount on green bonds. However, green bonds certified by an external reviewer enjoy a discount of about 6 bps. Furthermore, green bonds that obtain a Climate Bonds Initiative certificate show a discount of around 15 bps. The findings suggest that a universally accepted greenness measure can benefit the development of the green bond market.     

YouTubers’ networking activities during the 2016 South Korea earthquake

While YouTube has become an important social networking platform for risk and crisis communications, research into its role and use during environmental disasters has not been conducted. The present study investigates how Korean YouTubers reacted during the 2016 Gyeongju earthquakes. Two kinds of data were collected from the most popular YouTube clips on the earthquake (from AfreecaTV and YonHap news): the most frequently used words in the replies to the comments and the networked forums among YouTubers. Findings suggest that YouTube has become a channel for quickly increasing public awareness of crises and for promoting safety strategies. InDegree Centralization is higher in professional videos. Hierarchy measure’s value is one, which means the reply-to network is not two-way. There is sparse close-knittedness in amateur videos. Community clusters emerge in amateur videos over time. The results also reveal that YouTubers on AfreecaTV are more likely to express emotional opinions than their counterparts on YonHap news are.     

Pay dispersion among the top management team and outside directors: Its impact on firm risk and firm performance

Two key groups central to improving firm performance are the top management team (TMT) and the board of directors. Executives undertake strategic actions, whereas board members fulfill their resource provision and monitoring roles. Drawing on tournament theory and equity theory, we propose that high pay dispersion among outside directors and the TMT is positively associated with strategic risk, whereas high (low) TMT pay dispersion and low (high) outside director pay dispersion are positively associated with firm performance. Our predictor is the unexplained component of horizontal pay dispersion, or the residual of pay dispersion resulting from regressing pay on observable firm, industry, period, and individual characteristics. Our results highlight the importance of unexplained pay dispersion for TMTs, but not for boards of directors, in improving firm performance.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

Does local political support influence financial markets? A study on the impact of job approval ratings of political representatives on local stock returns

Using data on job approval ratings of governors, U.S. senators, and the president, we find that firms located in states with high approval ratings outperform firms located in states with low approval ratings by .64% per month. Furthermore, this relationship is stronger when investors are actively involved in politics, when local politicians are closer to the center of political power, for small firms that have a larger proportion of local investors, and for financially strong areas where investors are ready to execute investments in local stocks. Overall, our study shows that investors’ political sentiment is important in determining stock returns.