Associate Professor; Ph.D. Coordinator, Operations Management | Operations Management
Atlanta, GA, UNITED STATES
Dr. Hora's research addresses managing operational risk through capturing knowledge from low-frequency high-impact operational failures.
Journal of Operations Management
Production and Operations Management Journal
AMA Entrepreneurial Marketing Special Interest Group, with Devkamal Dutta, “From Invention to Commercialization: Technology Ventures and the Role of Alliance Partnerships”
Product Development and Management Association (PDMA) Annual Conference, with Jennifer Bailey and Cheryl Gaimon, "The Impact of Exploration, Exploitation, Learning from Success and Learning from Failure on Generating Breakthrough Innovations"
Chartered Financial Analyst
MBA, Finance, General
Ph.D., Operations Management
Dissertation Title: “Learning from Rare Operational Failure”
Business Daily online
Shoe manufacturer, Bata Kenya, last week asked customers who had bought low quality products from its stores to submit refund claims, days after consumers had taken to social media to air their grievances about its shoes, harming its brand trust.view more
Product recalls are on the rise, according to media and research reports, in industries as diverse as automobiles, electronics, food products, medical devices, pharmaceuticals, and toys. Deaths, injuries, and property damage resulting from defective products cost the United States more than US$800 billion annually, the Consumer Product Safety Commission (CPSC) estimates.view more
Argote, L. and Hora, M.
Organizational learning includes processes of creating, retaining and transferring knowledge and has implications for the performance and competitiveness of organizations. Given the knowledge‐based view of resources inherent in management of technology (MOT), in this study, we adopt an organizational learning framework that considers knowledge to be embedded in three major components of organizations—members, tasks and tools—and the networks formed by crossing them. We present research related to these components that is most applicable to MOT. In suggesting future research in MOT, we explicate the framework further by proposing that learning occurs in an organizational context.
Hora, M. and Klassen, R.
Risks arising from operations are increasingly being highlighted by managers, customers, and the popular press, particularly related to large-scale (and usually low-frequency) losses. If poorly managed, the resulting disruptions in customer service and environmental problems incur enormous recovery costs, prompt large legal liabilities, and damage customer goodwill and brand equity. Yet, despite conventional wisdom that firms should improve their own operations by observing problems that occur in others’ processes, significant operational risks appear to be ignored and similar losses recur. Using a randomized vignette-based field experiment, we tested the influence of organization-level factors on knowledge acquisition. Two organization-level factors, namely perceived operational similarity, and to a lesser extent, market leadership, significantly influenced the risk manager's likelihood of acquiring knowledge about possible causes that triggered another firm's operational loss. These findings suggest that senior managers need to develop organizational systems and training to expand the screening by risk managers to enhance knowledge acquisition. Moreover, industry and trade organizations may have a role in fostering the transfer of knowledge and potential learning from operational losses of firms.
Hora, M., Bapuji, H. and Roth, A.
This research identifies and tests key factors that can be associated with time to recall a product. Product recalls due to safety hazards entail societal costs, such as property damage, injury, and sometimes death. For firms, the related external failure costs are many, including the costs of recalling the product, providing a remedy, meeting the legal liability, and repairing damage to the firm's reputation. The recent spate of product recalls has shifted attention from why products are recalled to why it takes so long to recall a defective product that poses a safety hazard. To address this, our research subjects to empirical scrutiny the time to recall and its relationship with recall strategies, source of the defect and supply chain position of the recalling firm. We develop and verify our conceptual arguments in the U.S. toy industry by analyzing over 500 product recalls during a 15-year period (1993–2008). The empirical results indicate that the time to recall, as measured by difference between product recall announcement date and product first sold date, is associated with (1) the recall strategy (preventive vs. reactive) adopted by the firm, (2) the type of product defect (manufacturing defect vs. design flaw), and (3) the supply chain entity that issues the recall (toy company vs. distributor vs. retailer). Our results provide cues that could trigger a firm's recognition of factors that increase the time to recall.