Shashank Vaid

414 total citations
14 papers, 303 citations indexed

About

Shashank Vaid is a scholar working on Strategy and Management, Accounting and Organizational Behavior and Human Resource Management. According to data from OpenAlex, Shashank Vaid has authored 14 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Strategy and Management, 4 papers in Accounting and 3 papers in Organizational Behavior and Human Resource Management. Recurrent topics in Shashank Vaid's work include Corporate Finance and Governance (4 papers), Innovation and Knowledge Management (3 papers) and Data-Driven Disease Surveillance (2 papers). Shashank Vaid is often cited by papers focused on Corporate Finance and Governance (4 papers), Innovation and Knowledge Management (3 papers) and Data-Driven Disease Surveillance (2 papers). Shashank Vaid collaborates with scholars based in Canada, United States and United Kingdom. Shashank Vaid's co-authors include Mohit Bhandari, Stefano Puntoni, Michael Ahearne, Ryan Krause, Vikas Khanduja, Benson Honig, Nathaniel N. Hartmann, Johannes Habel, Naveen Donthu and Katina Michael and has published in prestigious journals such as Journal of Marketing, Journal of Bone and Joint Surgery and Journal of Business Research.

In The Last Decade

Shashank Vaid

11 papers receiving 295 citations

Peers

Shashank Vaid
Bahjat Fakieh Saudi Arabia
Anasse Bari United States
Waleed Iqbal United Kingdom
James Scheibner Australia
Yannet Interian United States
Shashank Vaid
Citations per year, relative to Shashank Vaid Shashank Vaid (= 1×) peers Ankita Srivastava

Countries citing papers authored by Shashank Vaid

Since Specialization
Citations

This map shows the geographic impact of Shashank Vaid's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shashank Vaid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shashank Vaid more than expected).

Fields of papers citing papers by Shashank Vaid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shashank Vaid. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shashank Vaid. The network helps show where Shashank Vaid may publish in the future.

Co-authorship network of co-authors of Shashank Vaid

This figure shows the co-authorship network connecting the top 25 collaborators of Shashank Vaid. A scholar is included among the top collaborators of Shashank Vaid based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shashank Vaid. Shashank Vaid is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Habel, Johannes, et al.. (2025). Sales Pipeline Technology: Automated Lead Nurturing. Journal of Marketing. 89(5). 66–87. 6 indexed citations
2.
Vaid, Shashank, Stefano Puntoni, Benson Honig, & Katina Michael. (2025). In This Special Issue: When Attention is All Marketers Need—Artificial Intelligence in Marketing. 6(3). 242–249.
5.
Vaid, Shashank, Michael Ahearne, Benson Honig, & Ryan Krause. (2023). Customer-related executive leadership turnover and firm performance: A dilemma of firm-level human resource contingencies. Journal of Business Research. 159. 113759–113759. 2 indexed citations
6.
Vaid, Shashank & Naveen Donthu. (2023). When injured product users may also stay satisfied: A macro-level analysis. Journal of Business Research. 162. 113887–113887. 1 indexed citations
7.
Vaid, Shashank, et al.. (2023). Artificial intelligence and empirical consumer research: A topic modeling analysis. Journal of Business Research. 166. 114110–114110. 43 indexed citations
8.
Vaid, Shashank, Michael Ahearne, & Ryan Krause. (2021). Operations‐Related Structural Flux: Firm Performance Effects of Executives’ Appointments and Exits. Production and Operations Management. 30(7). 2188–2210. 8 indexed citations
9.
Vaid, Shashank, et al.. (2020). Deep learning COVID-19 detection bias: accuracy through artificial intelligence. International Orthopaedics. 44(8). 1539–1542. 149 indexed citations
10.
Vaid, Shashank, et al.. (2020). Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America. Journal of Bone and Joint Surgery. 102(13). e70–e70. 34 indexed citations
11.
Vaid, Shashank, et al.. (2020). Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America. International Orthopaedics. 44(8). 1581–1589. 32 indexed citations
12.
Vaid, Shashank & Benson Honig. (2020). The influence of investors’ opinions of human capital and multitasking on firm performance: a knowledge management perspective. Journal of Knowledge Management. 24(7). 1585–1603. 8 indexed citations
13.
Vaid, Shashank & Michael Ahearne. (2020). The instantaneous commitment effect: developing stakeholder orientation among managers. AMS Review. 11(1-2). 162–179.
14.
Vaid, Shashank, Michael Ahearne, & Ryan Krause. (2019). Joint marketing and sales appointment: Uncertainty from intertwining of marketing and sales in one position. Industrial Marketing Management. 85. 221–239. 18 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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