A new integrated model for multitasking during web searching

Investigating multitasking information behaviour, particularly while using the web, has become an increasingly important research area. People s reliance on the web to seek and find information has encouraged a number of researchers to investigate the characteristics of information seeking behaviour and the web seeking strategies used. The current research set out to explore multitasking information behaviour while using the web in relation to people s personal characteristics, working memory, and flow (a state where people feel in control and immersed in the task). Also investigated were the effects of pre-determined knowledge about search tasks and the artefact characteristics. In addition, the study also investigated cognitive states (interactions between the user and the system) and cognitive coordination shifts (the way people change their actions to search effectively) while multitasking on the web. The research was exploratory using a mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, pre-interviews, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Based on the working memory test, the participants were divided into two groups, those with high scores and those with lower scores. Similarly, participants were divided into two groups based on their flow state scale tests. All participants searched information on the web for four topics: two for which they had prior knowledge and two more without prior knowledge. The results revealed that working memory capacity affects multitasking information behaviour during web searching. For example, the participants in the high working memory group and high flow group had a significantly greater number of cognitive coordination and state shifts than the low working memory group and low flow group. Further, the perception of task complexity was related to working memory capacity; those with low memory capacity thought task complexity increased towards the end of tasks for which they had no prior knowledge compared to tasks for which they had prior knowledge. The results also showed that all participants, regardless of their working memory capacity and flow level, had the same the first frequent cognitive coordination and cognitive state sequences: from strategy to topic. In respect of disciplinary differences, accountants rated task complexity at the end of the web seeking procedure to be statistically less significant for information tasks with prior knowledge compared to the participants from the other disciplines. Moreover, multitasking information behaviour characteristics such as the number of queries, web search sessions and opened tabs/windows during searches has been affected by the disciplines. The findings of the research enabled an exploratory integrated model to be created, which illustrates the nature of multitasking information behaviour when using the web. One other contribution of this research was to develop new more specific and closely grounded definitions of task complexity and artefact characteristics). This new research may influence the creation of more effective web search systems by placing more emphasis on our understanding of the complex cognitive mechanisms of multitasking information behaviour when using the web

An investigation of multitasking on the web: key findings

Introduction. This paper presents key findings from a study exploring how multitasking information behaviour is affected by people’s working memory capacity and the flow they experience during the searching process. Method. The research is exploratory using a pragmatic, mixed method approach. 30 study participants, 10 psychologists, 10 accountants and 10 mechanical engineers, conducted Web searches on four information topics. The data collection tools used were: pre and post questionnaires, pre interviews, working memory test, the flow state scale of Jackson and Marsh (1996), audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Results. The results suggested that people with high working memory, high flow and mechanical engineers generated more cognitive coordination and cognitive state shifts than people with low working memory, low flow, accountants and psychologists. The most frequent cognitive state and coordination shift for all groups was from strategy to information topic. Low working memory participants rated task complexity at the end of the procedure more highly for tasks without prior knowledge compared to tasks with prior knowledge. Participants with high flow levels experienced a greater change of knowledge for information tasks without prior knowledge compared to participants with low flow. The degree of change of knowledge for participants with high flow was higher for tasks without prior knowledge rather than for tasks with prior knowledge

Critical events and social capital of family businesses

Our study is set to investigate the way critical events influence social capital of family firms. We focus on macro-economic shocks (Hoffman et al., 2001; Ramey, 2016) that can trigger organisational transformation (Fligstein, 1991; Tan & See, 2004). We examine this phenomenon in the context of family-owned SMEs (Gersick et al., 1997; Lansberg, 1999), experiencing and dealing with a financial crisis as an instance of such shock. We consider family businesses as businesses in which the family has a hand-on involvement in the management of the business (Astrachan et al., 2002; Shanker & Astrachan, 1996). We examine social capital at the organisational level, which refers to resources an organisation accumulates as part of relations within and beyond its boundaries (Fischer & Pollock, 2004; Herrero & Hughes, 2019; Zahra, 2010). We consider the structural and relational properties of social capital (Moran, 2005; Nahapiet & Ghoshal, 1998). Structural social capital relates to the configuration of linkages between actors such as individuals and organisations upstream or downstream the value chain (Burt, 1992; Granovetter, 1985). Relational social capital focuses on the normative conditions that drive the relationships between actors in networks (Nahapiet & Ghoshal, 1998). Considering the above, we address the following research question: How do critical events influence a family firm’s structural and relational social capital

Social capital of family businesses: The influence of critical events in the macro-environment

Our study is set to investigate the way critical events influence social capital of family firms. We focus on macro-economic shocks (Hoffman, 1999; Ramey, 2016) that can trigger organisational transformation (Fligstein, 1991; Tan & See, 2004). We examine this phenomenon in the context of family-owned SMEs (Gersick et al., 1997; Lansberg, 1999), experiencing and dealing with a financial crisis as an instance of such shock. We consider family businesses as businesses in which the family has a hand-on involvement in the management of the business (Astrachan et al., 2002; Shanker & Astrachan, 1996). We examine social capital at the organisational level, which refers to resources an organisation accumulates as part of relations within and beyond its boundaries (Fischer & Pollock, 2004; Herrero & Hughes, 2019; Zahra, 2010). We consider the structural and relational properties of social capital (Moran, 2005; Nahapiet & Ghoshal, 1998). Structural social capital relates to the configuration of linkages between actors such as individuals and organisations upstream or downstream the value chain (Burt, 1992; Granovetter, 1985). Relational social capital focuses on the normative conditions that drive the relationships between actors in networks (Nahapiet & Ghoshal, 1998). Considering the above, we address the following research question: How do critical events influence a family firm’s structural and relational social capital