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Top1. Introduction
Data has been growing in size and complexity over the past few decades to a point where it has become difficult for businesses to convert data into useful information. In 2005, Roger Magoulas from O'Reilly media came up with the term “big data” to describe data sets that are so large, they become nearly impossible to analyze using traditional management systems (Agrawal et al., 2008; Ghaleb et al., 2021). Big data is a term for data sets that are so large and complex that traditional data processing applications are inadequate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy (McAfee et al., 2012; Ur Rehman et al., 2016). Data has infiltrated nearly every aspect of our lives. “Big data” refers to information sets that are too large and complex to be managed by traditional means. More and more data are being generated across practically all areas of society on a global scale. When leveraged correctly, big data has the potential to generate new insights, streamline decision-making, and improve the quality of products and services (Kim et al., 2014; Gunasekaran et al., 2017). According to a classic Chinese saying, “the people see food as their first want.” This means that we are innately programmed to seek out tasty, wholesome, and fresh meals to survive. And since food is such a high demand necessity, it's no surprise that the food industry is the most major and significant industry in the world. The food industry includes farming, food producers, food manufacturers, packers, cooks, food and beverage enterprises, shipping businesses, supermarkets, and dining establishments (Madaan et al., 2021).
Big data and analytics have been helping a wide range of organisations, including the food sector, to develop and evolve in today’s business environment. Feleen & David (2021) note that although big data has been around for a while, the food industry has only recently begun to effectively utilise it. The food business is facing a unique issue where, due to its potential in understanding the market, customer behaviour, and buying patterns, big data adoption and analysis has become extremely important. It is vital for food businesses to keep up with changing customer tastes over time in order to stay current in the market (Panpatte & Ganeshkumar, 2021; Garwal et al., 2020).
When businesses can analyse information quickly and efficiently, they are able to make better and faster decisions. In-memory analytics and the ability to analyse new data sources gives businesses the potential to provide customers with what they want. Using analytics to measure client requirements and satisfy them with new products and services is key to success (David 2020b). Big data analytics is a powerful tool that can help companies make better decisions. The food industry has begun to adopt this technology in order to stay competitive, but there are many factors involved in this adoption. By understanding these factors, we can better understand the industry and its future. This study used the technology-organizational-environmental model to analyze the factors involved in the adoption of big data analytics by the food industry (Maroufkhani et al., 2022a).