an article by Vladlena Benson and Chris Hand (Kingston Business School, UK) and Jean-Noel Ezingeard (Manchester Metropolitan University, UK) published in Information Technology & People Volume 32 Issue 4 (2019)
Abstract
Purpose
Social media users’ purchasing behaviour is yet to be fully understood by research. The purpose of this paper is to investigate how purchase intention is affected by social media user traits, cognitive factors (such as perceived control and trust) and individual beliefs, such as risk propensity and trustworthiness.
Design/methodology/approach
The authors propose and empirically test a model of purchase intention on social platforms. The study of over 500 active social media users finds the links between risk propensity, trust, technical efficacy and perceived control and explores the moderating effect of age and gender.
Findings
Purchase intention on social platforms is influenced by demographic factors, cognitive factors and beliefs. Both age and gender moderate the effects of beliefs and cognitive factors: age is a determinant of purchase intention for men, while beliefs are significant for younger women and cognitive factors are significant for older women.
Research limitations/implications
This study involved a cross-sectional design via online survey of social networking users. Gender differences in purchase intentions are found which are, in turn, influenced by age. Further empirical testing of social purchase intention could include less experienced users or non-users.
Practical implications
The results of this study provide guidance for SNS providers and technology developers in social networking commerce in terms of the different drivers of purchase intention.
Originality/value
Social media users’ purchasing behaviour is yet to be fully understood. The study shows that purchase intention antecedents vary between genders and age groups of users. The identified connection between users’ perceptions of social networking sites (SNS) usage of personal information and purchase behaviour has an impact on the likelihood of user engagement in social transactions.
Showing posts with label social_network_analysis. Show all posts
Showing posts with label social_network_analysis. Show all posts
Monday, 14 October 2019
Thursday, 17 January 2019
Excessive social media use at work: Exploring the effects of social media overload on job performance
an article by Lingling Yu, Zhiying Liu and Junkai Wang (University of Science and Technology of China, Hefei, China) and Xiongfei Cao (Hefei University of Technology, China) published in Information Technology & People Volume 31 Issue 6 (2018)
Abstract
Purpose
The purpose of this paper is to explore the effects of excessive social media use on individual job performance and its exact mechanism. An extended stressor–strain–outcome research model is proposed to explain how excessive social media use at work influences individual job performance.
Design/methodology/approach
The research model was empirically tested with an online survey study of 230 working professionals who use social media in organizations.
Findings
The results revealed that excessive social media use was a determinant of three types of social media overload (i.e. information, communication and social overload). Information and communication overload were significant stressors that influence social media exhaustion, while social overload was not a significant predictor of exhaustion. Furthermore, social media exhaustion significantly reduces individual job performance.
Originality/value
Theory-driven investigation of the effects of excessive social media use on individual job performance is still relatively scarce, underscoring the need for theoretically-based research of excessive social media use at work. This paper enriches social media research by presenting an extended stressor–strain–outcome model to explore the exact mechanism of excessive use of social media at work, and identifying three components of social media-related overload, including information, communication and social overload. It is an initial attempt to systematically validate the casual relationships among excessive usage experience, overload, exhaustion and individual job performance based on the transactional theory of stress and coping.
Abstract
Purpose
The purpose of this paper is to explore the effects of excessive social media use on individual job performance and its exact mechanism. An extended stressor–strain–outcome research model is proposed to explain how excessive social media use at work influences individual job performance.
Design/methodology/approach
The research model was empirically tested with an online survey study of 230 working professionals who use social media in organizations.
Findings
The results revealed that excessive social media use was a determinant of three types of social media overload (i.e. information, communication and social overload). Information and communication overload were significant stressors that influence social media exhaustion, while social overload was not a significant predictor of exhaustion. Furthermore, social media exhaustion significantly reduces individual job performance.
Originality/value
Theory-driven investigation of the effects of excessive social media use on individual job performance is still relatively scarce, underscoring the need for theoretically-based research of excessive social media use at work. This paper enriches social media research by presenting an extended stressor–strain–outcome model to explore the exact mechanism of excessive use of social media at work, and identifying three components of social media-related overload, including information, communication and social overload. It is an initial attempt to systematically validate the casual relationships among excessive usage experience, overload, exhaustion and individual job performance based on the transactional theory of stress and coping.
Friday, 26 October 2018
Excessive social media use at work: Exploring the effects of social media overload on job performance
an article by Lingling Yu, Zhiying Liu and Junkai Wang (University of Science and Technology of China, Hefei, China) and Xiongfei Cao (Hefei University of Technology, Hefei, China) Information Technology & People Volume 31 Issue 6 (2018)
Abstract
Purpose
The purpose of this paper is to explore the effects of excessive social media use on individual job performance and its exact mechanism. An extended stressor–strain–outcome research model is proposed to explain how excessive social media use at work influences individual job performance.
Design/methodology/approach
The research model was empirically tested with an online survey study of 230 working professionals who use social media in organizations.
Findings
The results revealed that excessive social media use was a determinant of three types of social media overload (i.e. information, communication and social overload). Information and communication overload were significant stressors that influence social media exhaustion, while social overload was not a significant predictor of exhaustion. Furthermore, social media exhaustion significantly reduces individual job performance.
Originality/value
Theory-driven investigation of the effects of excessive social media use on individual job performance is still relatively scarce, underscoring the need for theoretically-based research of excessive social media use at work. This paper enriches social media research by presenting an extended stressor–strain–outcome model to explore the exact mechanism of excessive use of social media at work, and identifying three components of social media-related overload, including information, communication and social overload. It is an initial attempt to systematically validate the casual relationships among excessive usage experience, overload, exhaustion and individual job performance based on the transactional theory of stress and coping.
Abstract
Purpose
The purpose of this paper is to explore the effects of excessive social media use on individual job performance and its exact mechanism. An extended stressor–strain–outcome research model is proposed to explain how excessive social media use at work influences individual job performance.
Design/methodology/approach
The research model was empirically tested with an online survey study of 230 working professionals who use social media in organizations.
Findings
The results revealed that excessive social media use was a determinant of three types of social media overload (i.e. information, communication and social overload). Information and communication overload were significant stressors that influence social media exhaustion, while social overload was not a significant predictor of exhaustion. Furthermore, social media exhaustion significantly reduces individual job performance.
Originality/value
Theory-driven investigation of the effects of excessive social media use on individual job performance is still relatively scarce, underscoring the need for theoretically-based research of excessive social media use at work. This paper enriches social media research by presenting an extended stressor–strain–outcome model to explore the exact mechanism of excessive use of social media at work, and identifying three components of social media-related overload, including information, communication and social overload. It is an initial attempt to systematically validate the casual relationships among excessive usage experience, overload, exhaustion and individual job performance based on the transactional theory of stress and coping.
Friday, 5 October 2018
Evidence-informed policymaking and policy innovation in a low-income country: does policy network structure matter?
an article by Jessica C Shearer (PATH, USA) and John Lavis, Julia Abelson and Michelle Dion (McMaster University, Canada) and Gill Walt (London School of Hygiene and Tropical Medicine, UK) published in Evidence & Policy: A Journal of Research, Debate and Practice Volume 14 Number 3 (August 2018)
Abstract
The application of social network analysis to policy networks continues to grow, including the application of social network analysis tools and concepts in order to explain policy outcomes. Gaps in this field of study persist in terms of both policy issues studied, as well as types of polities or networks analysed.
This study extends previous research on the role of network structure in shaping policy outcomes by analysing network structure's effect on the use of research evidence by three health policy networks in Burkina Faso, a low-income West African country, and the resulting innovativeness of the policies made.
This comparative case study confirms certain hypotheses related to the effect of network closure and heterogeneity on evidence use and innovation; namely, that heterogeneous networks are more likely to be exposed to new ideas, and thus to use research evidence and adopt innovative policies. High levels of centralised control and power may support innovation when the new ideas are consistent with the dominant network paradigms; otherwise, new ideas may receive less traction.
These findings confirm previous research and point to opportunities to shape networks to achieve innovation and policy change based on the best evidence.
Full text (PDF 21pp)
Abstract
The application of social network analysis to policy networks continues to grow, including the application of social network analysis tools and concepts in order to explain policy outcomes. Gaps in this field of study persist in terms of both policy issues studied, as well as types of polities or networks analysed.
This study extends previous research on the role of network structure in shaping policy outcomes by analysing network structure's effect on the use of research evidence by three health policy networks in Burkina Faso, a low-income West African country, and the resulting innovativeness of the policies made.
This comparative case study confirms certain hypotheses related to the effect of network closure and heterogeneity on evidence use and innovation; namely, that heterogeneous networks are more likely to be exposed to new ideas, and thus to use research evidence and adopt innovative policies. High levels of centralised control and power may support innovation when the new ideas are consistent with the dominant network paradigms; otherwise, new ideas may receive less traction.
These findings confirm previous research and point to opportunities to shape networks to achieve innovation and policy change based on the best evidence.
Full text (PDF 21pp)
Monday, 3 December 2012
A diagnosis framework for identifying the current knowledge sharing activity status in a community of practice
Sung-jin Kim (GS Caltex Corporation, South Korea), Jong-yi Hong (Kyungnam University, South Korea) and Eui-ho Suh (Pohang University of Science and Technology, South Korea) published in Expert Systems with Applications Volume 39 Issue 18 (15 December 2012)
Abstract
The concept of Communities of Practice (CoPs) has been highlighted as an effective method for knowledge sharing in Knowledge Management (KM) and strategically utilized by many organisations.
Therefore, the need to diagnose knowledge sharing activities in CoPs has increased.
Previous research on CoP strategies has generally suggested broad guidelines without diagnosing the current knowledge sharing status of individual CoPs. Furthermore, diagnosis methodologies are not connected to strategic direction and require too much time and effort to conduct regularly.
The purpose of this paper is to develop a sustainable diagnosis framework for identifying knowledge sharing activities in CoPs using Social Network Analysis (SNA) and to suggest strategies for individual CoPs based on the proposed diagnosis framework.
Finally, we apply the proposed diagnosis framework to an industry case.
Highlights
► This research provides a general method to analyse knowledge sharing using SNA.
► This research tried to develop a diagnosis methodology using SNA to identify different CoP types.
► This research suggests customised strategies for individual CoP knowledge sharing activities.
Figures and tables from this article
Abstract
The concept of Communities of Practice (CoPs) has been highlighted as an effective method for knowledge sharing in Knowledge Management (KM) and strategically utilized by many organisations.
Therefore, the need to diagnose knowledge sharing activities in CoPs has increased.
Previous research on CoP strategies has generally suggested broad guidelines without diagnosing the current knowledge sharing status of individual CoPs. Furthermore, diagnosis methodologies are not connected to strategic direction and require too much time and effort to conduct regularly.
The purpose of this paper is to develop a sustainable diagnosis framework for identifying knowledge sharing activities in CoPs using Social Network Analysis (SNA) and to suggest strategies for individual CoPs based on the proposed diagnosis framework.
Finally, we apply the proposed diagnosis framework to an industry case.
Highlights
► This research provides a general method to analyse knowledge sharing using SNA.
► This research tried to develop a diagnosis methodology using SNA to identify different CoP types.
► This research suggests customised strategies for individual CoP knowledge sharing activities.
Figures and tables from this article
Monday, 12 November 2012
The role of scaffolding and motivation in CSCL
an article by Bart Rienties and Simon Lygo-Baker (University of Surrey, Guildford, UK), Bas Giesbers, Mien Segers, Wim Gijselaers and Dirk Tempelaar (Maastricht University, The Netherlands) published in
Computers & Education
Volume 59 Issue 3 (November 2012)
Abstract
Recent findings from research into Computer-Supported Collaborative Learning (CSCL) have indicated that not all learners are able to successfully learn in online collaborative settings. Given that most online settings are characterised by minimal guidance, which require learners to be more autonomous and self-directed, CSCL may provide conditions more conducive to learners comfortable with greater autonomy.
Using quasi-experimental research, this paper examines the impact of a redesign of an authentic CSCL environment, based upon principles of Problem-Based Learning, which aimed to provide a more explicit scaffolding of the learning phases for students. It was hypothesised that learners in a redesigned ‘Optima’ environment would reach higher levels of knowledge construction due to clearer scaffolding.
Furthermore, it was expected that the redesign would produce a more equal spread in contributions to discourse for learners with different motivational profiles.
In a quasi-experimental setting, 143 participants collaborated in an online setting aimed at enhancing their understanding of economics. Using a multi-method approach (Content Analysis, Social Network Analysis, measurement of Academic Motivation), the research results reveal the redesign triggered more equal levels of activity of autonomous and control-oriented learners, but also a decrease in input from the autonomous learners.
The main conclusion from this study is that getting the balance between guidance and support right to facilitate both autonomous and control-oriented learners is a delicate complex issue.
Highlights
► Most online settings have minimal guidance, which require learners to be autonomous.
► We examine impact of increased scaffolding of learning phases on knowledge construction.
► Redesign triggered more equal activity of autonomous and control-oriented learners.
► Redesign negatively impacted autonomous learners to lead discourse.
► Balance guidance and support more complex in authentic than experimental settings.
Abstract
Recent findings from research into Computer-Supported Collaborative Learning (CSCL) have indicated that not all learners are able to successfully learn in online collaborative settings. Given that most online settings are characterised by minimal guidance, which require learners to be more autonomous and self-directed, CSCL may provide conditions more conducive to learners comfortable with greater autonomy.
Using quasi-experimental research, this paper examines the impact of a redesign of an authentic CSCL environment, based upon principles of Problem-Based Learning, which aimed to provide a more explicit scaffolding of the learning phases for students. It was hypothesised that learners in a redesigned ‘Optima’ environment would reach higher levels of knowledge construction due to clearer scaffolding.
Furthermore, it was expected that the redesign would produce a more equal spread in contributions to discourse for learners with different motivational profiles.
In a quasi-experimental setting, 143 participants collaborated in an online setting aimed at enhancing their understanding of economics. Using a multi-method approach (Content Analysis, Social Network Analysis, measurement of Academic Motivation), the research results reveal the redesign triggered more equal levels of activity of autonomous and control-oriented learners, but also a decrease in input from the autonomous learners.
The main conclusion from this study is that getting the balance between guidance and support right to facilitate both autonomous and control-oriented learners is a delicate complex issue.
Highlights
► Most online settings have minimal guidance, which require learners to be autonomous.
► We examine impact of increased scaffolding of learning phases on knowledge construction.
► Redesign triggered more equal activity of autonomous and control-oriented learners.
► Redesign negatively impacted autonomous learners to lead discourse.
► Balance guidance and support more complex in authentic than experimental settings.
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