Artificial intelligence and internet of things in small and medium-sized enterprises: A survey

Identifying the configurational conditions for marketing analytics use in UK SMEs

“…Second, this study extends the scope of analytics research by conceptualizing and empirically demonstrating that the conditions leading to analytics applications can be asymmetrical, thus more complex than assumed by most analytics studies based on regressionbased methods (e.g., Gupta and George, 2016). An important implication of this study is the need to unearth the assumptions that underlie analytics studies and to consider the possibility Third, whilst SMEs are traditionally examined as one homogeneous group (e.g., Ferraris et al, 2019, Maroufkhani et al, 2020, Hansen and Bøgh, 2020, Dong and Yang, 2020, Liu et al, 2020, this study provides additional empirical evidence to support the idea that small and medium-sized firms could have distinctive patterns of IS adoption (e.g., Reyes et al, 2016, Gillon et al, 2014, Thong et al, 1996, Haase and Franco, 2011. The implications of this finding are twofold.…”

“…Based on the literature review, the following gaps concerning marketing analytics use are identified and will be addressed in this study: First, although studies have established the link between the use of business analytics and improved firm performance such as innovation (e.g., Duan et al, 2020), decision making effectiveness (e.g., Cao et al, 2015), supply chain performance (e.g., Zhan and Tan, 2020), and competitive advantages (e.g., Cao et al, 2019, WangYeoh et al, 2019, the majority of these studies are based on large companies and their findings should not be applied to SMEs directly without further investigation, as SMEs are not smaller versions of larger firms (O'Regan et al, 2005). Aside from only a few studies (e.g., Ferraris et al, 2019, Maroufkhani et al, 2020, Hansen and Bøgh, 2020, Liu et al, 2020, business/marketing analytics use and its effect on the performance of SMEs are yet to be fully investigated (e.g., Maroufkhani et al, 2020, Liu et al, 2020, Wang et al, 2018. Second, although prior studies have used configurational approaches to understand organizational relationships in SMEs (e.g., Hughes et al, 2019, Uwizeyemungu et al, 2018, Poorkavoos et al, 2016, Magistretti et al, 2020, no research has investigated how the configurations of multiple conditions affect business/marketing analytics use in SMEs.…”

“…de Haan et al, 2007, Haase andFranco, 2011) and tends to be associated with different patterns of IS investment and use (e.g. Gillon et al, 2014, Thong et al, 1996, Haase and Franco, 2011, Dong and Yang, 2020, almost all prior analytics studies have examined SMEs as one homogeneous group (e.g., Ferraris et al, 2019, Maroufkhani et al, 2020, Hansen and Bøgh, 2020, Liu et al, 2020. Thus, whether or not small and mediumsized firms differ in terms of marketing analytics use remains unexamined in empirical research.…”

“…SMEs, because of their small business size, generally lack resources and specialist expertise, thus tend to have difficulties exploiting analytics (Gillon et al, 2014, Liu et al, 2020, Maroufkhani et al, 2020, Hansen and Bøgh, 2020. Nevertheless, there is evidence in the literature to suggest that some SMEs have adopted business analytics to improve decision making and to gain competitive advantages (Ferraris et al, 2019, Dong and Yang, 2020, Liu et al, 2020 Ferraris et al, 2019, Maroufkhani et al, 2020, Hansen and Bøgh, 2020, Dong and Yang, 2020, Liu et al, 2020, there is evidence to suggest that small and medium-sized firms are significantly different (e.g. de Haan et al, 2007) and have distinctive patterns of IS adoption (e.g., Reyes et al, 2016, Gillon et al, 2014, Thong et al, 1996, Haase and Franco, 2011.…”

AI‐Enabled Sensing and Decision‐Making for IoT Systems

“…e selected studies cover the application of IoT in the pain assessment, and some discuss the enabling technologies for management of pain. Hansen and Bøgh [21] presented a detailed investigation and survey on how AI and IoT are among manufacturing SMEs and explored the existing opportunities and limitations for enabling predictive analytics. Initially, the overview of the IoT and AI-enabled system along with four capabilities are provided, and then review of the literature and its analysis is shown.…”