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PurposeThe COVID-19 pandemic impacted the food and beverage sector very severely. The complete breakdown of the supply chain and lack of customers was particularly challenging for start-ups in the industry. Those that survived were the ones who made a timely and smooth transition in business models to become more technology driven. However, the issues faced and the ground realities of the extent of struggle that these start-ups went through are less understood in the scholarly literature, with most accounts being anecdotal. The purpose of this paper is to address these issues.Design/methodology/approachThe present study attempts to bridge this gap by conducting a qualitative study to collect data from 35 owners/employees of food and beverage start-ups and using the grounded theory approach to code it and identify key themes.FindingsContent analysis of the 35 responses revealed three main themes: the impact of the COVID-19 pandemic on operations of food and beverage start-ups, challenges due to the onset of the COVID-19 pandemic and combating the pandemic, divided into seven subthemes: differences in operations pre- and post-COVID, key changes experienced in operations post-COVID, problems arising in operations due to the pandemic, problems in the use of digital marketing due to the pandemic, problems in the use of technological platforms due to the pandemic, using innovative approaches and technological innovations and using disruptive technologies.Originality/valueThe study contributes novel insights by investigating the changes experienced by food and beverage start-ups due to the pandemic, the innovations introduced by them and the perception about the role of disruptive technologies in their postpandemic operations of food and beverage start-ups.

This chapter attempts to study the intentions to use cloud-based CRM applications through a combination between a Technology Acceptance Model (TAM) and a Theory of Planned Behavior (TPB). To test the different links identified in the research model, a research questionnaire was prepared and sent to marketing managers within Saudi SMEs in Saudi Arabia. A total of 41 useful questionnaires were collected. The authors opted to the structural equation modeling (SEM) using the Partial Least Squares (PLS) to analyze data. The tests are prepared with XLstat software since it integrates both factor analysis and PLS modules. Among the main statistical analyses, the authors conclude that the TPB-TAM is suitable to study cloud CRM. From a managerial perspective, the authors expect that cloud CRM is perceived with good impression and that this new technology should be implemented strongly and gradually in SMEs to improve the quality of services provided to customers and organizations.