Management School seminars

'Social media and operations management: An example of automotive recall timing' seminar

Join our upcoming 'Social media and operations management: An example of automotive recall timing' hybrid seminar with Dr Christoph G. Schmidt.

Speaker: Dr Christoph G. Schmidt (Swiss Federal Institute of Technology Zurich)

Hosted by: University of Liverpool Management School's Operations and Supply Chain Management Group

Open to: OSCM Group staff and students, with no sign up needed

Date: Thursday 9 October 2023

Time: 12-2pm

Online: join Zoom meeting here

  • Passcode: VCm#BBa8

In person: Rendall Building, L69 7WW - Lecture Theatre 3


Abstract

In today’s interconnected economy, firms are less insulated from customer opinions and feedback than in the past. Social media platforms have enabled customers to voice their opinions about a firm’s products and actions.

In a series of research projects, we explore when and how the public engages on social media and how the reaction to firm events impacts decision-making and financial performance.

Product recalls, for example, are one of the most pivotal and prominent product quality decisions that firm leaders have to make.

While a burgeoning recall literature stream explores leading indicators and consequences of automotive recalls, research is silent on factors that influence the speed by which an automotive firm decides to recall defective cars.

Further, there has been limited research exploring how the textual sentiment of product complaints and social media comments about a firm may influence a firm’s product recall decision-making speed, though it presents an ideal context to explore how textual sentiment about a product and a firm may influence the timing of a firm’s quality decisions.

Using a published and novel auto recall timing data set and a recurrent event accelerated failure time model that incorporates 3,135 auto complaints, 7.37 million tweets, and 559 recalls for six firms across six years; we find that while the sentiment negativity of a product complaint is associated with slower recalls, sentiment negativity of tweets about the firm is associated with faster recalls.

A one standard deviation increase in past complaints neutrality is associated with a 16% faster time-to-recall and with a 20% faster time-to-recall for Twitter negativity.

Speaker

Christoph is a Senior Researcher and Lecturer at the Chair of Logistics Management at the Swiss Federal Institute of Technology Zurich (ETH Zurich) in Switzerland.

His main area of research is at the intersection of operations management and information systems, including blockchain and additive manufacturing, social media, data breaches, and risk management.

His work has appeared in Production and Operations Management, Journal of Operations Management, Journal of Supply Chain Management, Journal of Business Logistics, International Journal of Production Research, and other journals.

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