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Robotics at workplace: An integrated Twitter analytics – SEM based approach for behavioral intention to accept

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  • Sinha, Neena
  • Singh, Pragati
  • Gupta, Manali
  • Singh, Pratibha

Abstract

Robotics application has provided a fruitful combination for hybrid industry 4.0 teams wherein robotic systems are progressing their way into spaces shared with human workers. The advent of artificial intelligence has also instilled the feeling of distress and ambiguity among employees regarding their future. Such confusion has triggered a plethora of deliberations surrounding the possible receptivity and hostility towards these modern technologies in the digital era where people are articulating their opinions and experiences through social media communication. This study explores the antecedents of employees’ intention to accept robotics at workplace using two-step analyses: Twitter Analysis and Survey-based analysis. Around 121,750 tweets from 43,000 Twitter handles were evaluated in the form of descriptive analysis, geospatial analysis, network analysis and sentiment analysis. Thereafter, the conceptual model has been formulated and validated based on the extracted themes (anthropomorphism, technophobia and behavioral intention to accept robotics at workplace) by including 864 responses from an online survey conducted in India. The findings corroborated that anthropomorphism and technophobia significantly influence behavioral intention, and technophobia acts as a significant competitive mediator.

Suggested Citation

  • Sinha, Neena & Singh, Pragati & Gupta, Manali & Singh, Pratibha, 2020. "Robotics at workplace: An integrated Twitter analytics – SEM based approach for behavioral intention to accept," International Journal of Information Management, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:ininma:v:55:y:2020:i:c:s0268401219313441
    DOI: 10.1016/j.ijinfomgt.2020.102210
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    Cited by:

    1. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    2. Mengjun Li & Ayoung Suh, 2022. "Anthropomorphism in AI-enabled technology: A literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2245-2275, December.
    3. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).

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