As the availability of data is increasing everyday, the need to reflect on how to make these data meaningful and impactful becomes vital. Current data paradigms have provided data life cycles that often focus on data acumen and data stewardship approaches. In an effort to examine the convergence, tensions, and harmonies of these two approaches, a group of researchers participated in an interactive panel session at the Association of Information Science and Technology Annual meeting in 2019. The panel presenters described their various research activities in which they confront the challenges of the computational and social perspectives of the data continuum. This paper provides a summary of this interactive panel.
Information behavior, as a part of human behavior, has many aspects, including a cognitive aspect. Cognitive biases, one of the important issues in psychology and cognitive science, can play a critical role in people’s behaviors and their information behavior. This article discusses the potential relationships between some concepts of human information behavior and cognitive biases. The qualitative research included semistructured face-to-face interviews with 25 postgraduate students who were at the writing-up stage of their research. The participants were selected using a purposeful sampling process. Interviews were analyzed using the coding technique of classic grounded theory. The research framework was the Eisenberg and Berkowitz information behavior model. The relationships that are discussed in this article include those between the principle of least effort on the one hand and availability bias and ambiguity aversion on the other; value-sensitive design and reactance; willingness to return and availability bias; library anxiety and ambiguity aversion, status quo bias, and stereotypical bias; information avoidance and selective perception, confirmation bias, stereotypical bias, and conservatism bias; information overload and information bias; and finally, filtering and attentional bias.
E-commerce platforms generally provide various functions that can be adopted as signals for online sellers to convey implicit information to customers to promote sales. In this article, based on signaling theory and the stereotype content model, we categorize e-commerce signals into two types: signals of competence and signals of warmth. Signals of competence refer to the platform functions or mechanisms that can be leveraged by online sellers to indirectly convey information about their capabilities, such as promised delivery times and free return days. Signals of warmth refer to the platform functions or mechanisms that can be leveraged by online sellers to indirectly convey information about their kindness and care, such as the availability of online customer service agents. We explore the impacts of the two different types of signals on product sales for sellers with different credit rating levels. The empirical analysis is conducted on China's largest e-commerce platform, Taobao.com. The results show that online sellers with higher credit ratings should focus more on signals of warmth, while those with median and lower credit ratings should concentrate more on signals of competence. This study provides a theoretical framework that explains the effects of signaling on e-commerce platforms and may facilitate further exploration on signaling mechanisms. Our findings also provide implications for online sellers in terms of how to better utilize various signals as well as for e-commerce platforms on designing more effective supporting functions.
As a scientific field, scientific mapping offers a set of standardized methods and tools which can be consistently adopted by researchers in different knowledge domains to answer their own research questions. This study examined the scientific articles that applied science mapping tools (SMT) to analyze scientific domains and the citations of these application articles. To understand the roles of these application articles in scholarly communication, we analyzed 496 application articles and their citations from 14 SMT by classifying them into library and information science (LIS) and other fields (non-LIS) in terms of both publication venues and analyzed domains. In our study, we found that science mapping, a topic that is deeply situated in the LIS field, has gained increasing attention from various non-LIS scientific fields over the last few years, especially since 2012. Science mapping application studies practically grew up in LIS domain and spread to other fields. The application articles within and outside of the LIS fields played different roles in advancing the application of science mapping and knowledge discovery. Especially, we have discovered the important role of articles, which studied non-LIS domains but published in LIS journals, in advancing the application of SMTs.
This article aims to review the important roles of health knowledge organization systems (KOSs) during the COVID-19 pandemic. Different types of knowledge organization systems, including term lists, synonym rings, thesauri, subject heading systems, taxonomies, classification schemes, and ontologies are widely recognized and applied in both modern and traditional information systems. Apart from their usage in the management of data, information, and knowledge, KOSs are seen as valuable components for large information architecture, content management, findability improvement, and many other applications. After introducing the challenges of information overload and semantic conflicts, the article reviews the efforts of major health KOSs, illustrates various health coding schemes, explains their usages and implementations, and reveals their implications for health information exchange and communication during the COVID-19 pandemic. Some general examples of the applications, services, and analysis powered by KOSs are presented at the end. As revealed in this article, they have become even more critical to aid the frontline endeavors to overcome the obstacles due to information overload and semantic conflicts that can occur during devastating historic and worldwide events like the COVID-19 pandemic.
The entrepreneurship has positive and significant connection with economic growth. Competition would be increased by new entrants in the market; then, social welfare would be improved. Thus, positive entrepreneurship policies are often linked to increased social welfare by authorities. In this paper, we focus on a certain case where potential entrepreneurs are employees of existing firms to test the above ideas. The purpose of our research is to assess the variation of social welfare in the context of employer-restricted separation. Therefore, the model of Cournot competition where employees constitute the only entry threat was used in this paper. The results demonstrate that social welfare would not always be improved even in a good entrepreneurial context. If the deterring strategy is present, the relationship between positive entrepreneurship policies and increased social welfare might not hold, or would depend on the different strategies adopted by the incumbent. Therefore, the sustainability of a positive entrepreneurship policy would be impaired by incumbent firms.
This paper mainly studies whether and how stock prices fluctuate around their intrinsic values. Based on data from 10 stock markets for the period between 2000 and 2018, we demonstrate that the relative price fluctuates around and approaches the intrinsic value in the long term. For the ten markets, the relative price crosses the intrinsic value on average once in 3 ∼ 4 years. Profitability growth is a key factor in rising stock prices, but the level of valuations in the market has a regulatory effect to the growth of price in the future: For every 1 % increase in valuation, the price tends to decline by 0.26% in the next year, 0.74% in the next 3 years.
Material incentive is the main motivation for solvers to attend crowdsourcing tasks. So raising the bidding success rate is benefit to inspire the solvers attendance’ and increase the answering quality. This paper analyzes the effect of participation experience, task-fit capability, participation strategy and task attribute on the solvers bidding success by the solvers attending the series tasks of Tripadvisor. The results show that: 1) Participation times enrich the participation experiences and promote the bidding success, while bidding success times and last performances lower the bidding success because of the cognitive fixation; 2) The chance of bidding success will be increase when the solver own high task-fit capability; 3) The relationship between task submit sequence and bidding success is the type of reverse U shape, and the optimal submit sequence rate on the top of the reverse U shape; 4) Higher task difficulty lower bidding success, while higher task density easier bidding success.
A parameter estimation method, called PMCMC in this paper, is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps. There is a closed form solution to term structure of interest rates under Markov regime. However, the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM) in the case of adding jumps. Although the difficulty of parameter estimation greatly prevents from researching models, we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility. The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR. Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.
Understanding the satisfaction impact factors of China-Eurasia Expo is important to hold and improve the Expo. This paper divides the impact factors of satisfaction into local residents and exhibitors’ aspects. Firstly, this paper constructs a five-dimension conceptual model to measure the local residents’ satisfaction which consists of the degree of promoting economic development, environmental protection, cultural quality, urban convenience and urban brand image of the China-Eurasia Expo. 898 valid questionnaires were collected and structural equation model (SEM) was used to validate the constructed model and the proposed hypotheses were proved; the path coefficients of cultural quality, urban convenience and urban brand image to locals’ satisfaction are all greater than 0.90, indicating that they have high impacts on local residents’ satisfaction, while the path coefficient of the degree of promoting economic development to residents’ satisfaction is 0.695, indicating a relatively low impact. Secondly, this paper constructs a five-dimension conceptual model of exhibitors’ satisfaction which includes infrastructure, management level, service quality, organizing effect, and advancement. 708 valid questionnaires were collected and SEM was used to valid the constructed model and the proposed hypotheses. The results show that the five path coefficients to exhibitors’ satisfaction are higher than 0.7, all hypotheses were proved.