Search

The objective of this paper is to identify the dynamic structure of several time-dependent, discipline-level citation networks through a path-based method. A network data set is prepared that comprises 27 subjects and their citations aggregated from more than 27,000 journals and proceedings indexed in the Scopus database. A maximum spanning tree method is employed to extract paths in the weighted, directed, and cyclic networks. This paper finds that subjects such as Medicine, Biochemistry, Chemistry, Materials Science, Physics, and Social Sciences are the ones with multiple branches in the spanning tree. This paper also finds that most paths connect science, technology, engineering, and mathematics ( STEM) fields; 2 critical paths connecting STEM and non- STEM fields are the one from Mathematics to Decision Sciences and the one from Medicine to Social Sciences. [ABSTRACT FROM AUTHOR]

Richer forms of online reviews such as videos or follow‐on reviews convey 'additional information and can attract consumers' attention. However, prior studies focused mostly on the relationship between aggregated online reviews and sales. This paper investigates the impact of online review richness (i.e., reviews containing videos or follow‐on reviews) on sales. Leveraging attribute substitution theory, we conjecture that online review richness can provide heuristic cues in the online shopping environment to help consumers make better purchase decisions. Using data from JD.com, we found that reviews containing either videos or follow‐on reviews positively affect sales. In addition, different product types can also serve as heuristic cues to replace target cues, which can further affect how different forms of online review richness affect sales. We found that the impact of online review richness on sales is stronger for utilitarian products than for hedonic products, and stronger for negatively commented products than for positively commented products. Moreover, we conducted two online experiments and confirmed that the causal relationship is from online review richness to sales. The research findings offer practical implications for online retailers and constitute one of the first steps toward a better understanding of the relationship between online review richness and sales. [ABSTRACT FROM AUTHOR]

Entrepreneurs are showing an increasing focus on understanding and managing their social media strategies to optimize the success of their crowdfunding campaigns. While much of the current crowdfunding literature focuses on the roles of social media engagement in the funding performance of crowdfunded projects, in this study, drawing on social media engagement theory, we examine how product and entrepreneur characteristics moderate the influence of social media engagement on funding performance in the reward‐based crowdfunding. Using a dataset of technology crowdfunded projects, we investigated whether Facebook and Twitter engagements affect funding outcomes and if so, how the two interact with each other and their influences vary by project type (hardware and software) and entrepreneur characteristics (gender, experience, and social capital). We found that both Facebook and Twitter engagements positively affect funding, but the two weaken each other's impact, particularly for hardware products. Additionally, Facebook engagements had a larger effect on funding outcomes in the early days of a campaign driven by its prelaunch efforts, whereas Twitter engagements had a larger impact in later days. Furthermore, our findings indicated that Facebook engagement is more influential for hardware products. An entrepreneur's internal social capital built inside the crowdfunding platform also weakened the effects of Facebook engagements generated outside the platform, whereas Twitter engagements on subsequent funding had less influence on experienced entrepreneurs. Our findings suggest that Facebook mainly serves as a channel to show the significant commitment of entrepreneurs to their projects and increase persuasiveness, while Twitter helps to raise awareness by broadcasting crowdfunding campaigns among potential investors. [ABSTRACT FROM AUTHOR]

This study employs a panel threshold regression model to test whether the patent h-index has a threshold effect on the relationship between patent citations and market value in the pharmaceutical industry. It aims to bridge the gap in extant research on this topic. This study demonstrates that the patent h-index has a triple threshold effect on the relationship between patent citations and market value. When the patent h-index is less than or equal to the lowest threshold, 4, there is a positive relationship between patent citations and market value. This study indicates that the first regime (where the patent h-index is less than or equal to 4) is optimal, because this is where the extent of the positive relationship between patent citations and market value is the greatest. [ABSTRACT FROM AUTHOR]

The success of an enterprise information retrieval system is determined by interactions among three key entities: the search engine employed; the service provider who delivers, modifies, and maintains the engine; and the users of the service within the organization. Evaluations of an enterprise search have predominately focused on the effectiveness and efficiency of the engine, with very little analysis of user involvement in the process, and none on the role of service providers. We propose and evaluate a model of costs and benefits to a service provider when investing in enhancements to the ranking of documents returned by their search engine. We demonstrate the model through a case study to analyze the potential impact of using domain experts to provide enhanced mediated search results. By demonstrating how to quantify the cost and benefit of an improved information retrieval system to the service provider, our case study shows that using the relevance assessments of domain experts to rerank original search results can significantly improve the accuracy of ranked lists. Moreover, the service provider gains substantial return on investment and a higher search success rate by investing in the relevance assessments of domain experts. Our cost and benefit analysis results are contrasted with standard modes of effectiveness analysis, including quantitative (using measures such as precision) and qualitative (through user preference surveys) approaches. Modeling costs and benefits explicitly can provide useful insights that the other approaches do not convey. [ABSTRACT FROM AUTHOR]