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The use of information and communication technology (ICT) can be accompanied by the epiphenomenon of ICT-related overload, or the emotional and cognitive state that occurs when individuals are unable to efficiently retrieve and process information delivered by or associated with these technologies. While prior research tends to ascribe this phenomenon to the amount of information delivered, this study presents and provides significant empirical support for an expanded cognitive perspective of ICT-related overload, which views individuals' information-processing capabilities as being reliant on differences in mental representations associated with cultural, demographic, and experiential factors. Specifically, based on a survey with 1,004 mobile phone users, we find that (1) polychronic individuals experience less ICT-related overload than monochronics; (2) memories of past emotional and cognitive overload increase ICT-related overload; and (3) age has inverse effects on different overload dimensions. Altogether, our findings challenge myths about information overload and multitasking, support a multidimensional conceptualization of ICT-related overload, and suggest ways that managers can reduce overload and leverage polychronicity.

Although chatbots are increasingly deployed in customer service to reduce the burden of human labor and sometimes replace human employees in online shopping, there remains the challenge of ensuring consumers’ service evaluation and purchase decisions after chatbot service. Anthropomorphism, referring to human-like traits exhibited by non-human entities, is considered a key principle to facilitate customers’ positive evaluation of chatbot service and purchase decisions. However, equipping chatbots with anthropomorphism should be planned and rolled out cautiously because it could be both advantages to building customer trust and disadvantages for increasing customer overload. To understand how customers process and react to chatbot anthropomorphism, this study applied Wixom and Todd’s model and social information processing theory which guide this study to examine how object-based social beliefs (i.e., chatbot warmth and chatbot competence) of anthropomorphic chatbot influence service evaluation and customer purchase by generating behavioral beliefs (i.e., trust in chatbot and chatbot overload). The research model was examined with a “lab–in–the–field” experiment of 212 samples and two scenario-based experiments of 124 samples and 232 samples. The results showed that chatbot warmth and competence had significant effects on trust in chatbot and chatbot overload. Trust in chatbot and chatbot overload further significantly impact service evaluation and then customer purchase. Implications for theory and practice are discussed.