Bouncing back from a sudden-onset extreme event: exploring retail enterprises’ resilience capacity

Abstract

ABSTRACTA feature of recent decades has been the sudden and unexpected occurrence of catastrophic events seriously affecting people and territories. From an economic viewpoint, this has led scholars to pay increasing attention to factors and determinants taking enterprises face-to-face with extreme and catastrophic events, through the resilience lens. In this context, this study aims to contribute to the literature on resilience to natural disasters which is currently still limited in the business and management fields, both theoretically and empirically. This is particularly true as regards retailing, despite the key role played by retail in the aftermath and recovery periods following on from sudden-onset extreme events such as earthquakes.The 2012 Emilia earthquake is a case in point with which to explore small retail enterprises’ resilience to sudden-onset disasters. Specifically, our empirical research consisted of administering a structured questionnaire to a sample of small retail enterprises which experienced an earthquake. The unit of analysis adopted was the retail enterprise. Data was processed applying Covariance-Based Structural Equation Modeling (CB-SEM). The structural model aims to verify the impact of sales capabilities, market orientation and networking capabilities on the resilience capacity of retail enterprises affected by an extreme event, controlling for certain financial indicators such as suppliers’ payment timeframes and the use of debt capital, as well as respondent age and gender. The findings show that all the antecedents analysed exert a significant and positive effect on small retail enterprises’ resilience capacity and ability to bounce back from natural disasters. Moreover, suppliers’ payment timeframes showed a direct relationship with retail enterprises’ resilience capacity, with lower use of debt capital equalling higher retail business resilience. Age and gender do not exert any significant effect. Scientific, managerial and public policy implications are derived.Abbreviation: SEM