Moutusy Maity, Arunima Shah and Ankita Misra (Indian Institute of Management, Lucknow, India) and Kallol Bagchi (University of Texas at El Paso, Texas, USA) published in Information Technology & People Volume 32 Issue 1 (2019)
Abstract
Purpose
The purpose of this paper is to identify a model that provides explanations for normative behavior in information technology (IT) use, and to test the model across two different types of normative behavior (i.e. green information technology (GIT), and digital piracy (DP)).
Design/methodology/approach
The proposed model is based on the norm activation model (NAM) and the unified theory of acceptance and use of technology model (UTAUT). A total of 374 and 360 usable responses were obtained for GIT and DP, respectively. The authors use the SEM technique in order to test the proposed model on the two sub-samples.
Findings
Findings from the proposed model show that DP users’ personal norm (PN) negatively impacts behavioral intention and actual behavior. These findings indicate that users of IT who indulge in DP understand that use of pirated software may not be a socially approved behavior but they still indulge in it because their PNs are not aligned with social expectations. GIT users’ PN positively impacts behavioral intention and actual behavior, and the relationship is stronger for behavioral intention than for actual behavior.
Research limitations/implications
The sample consists of college students and working professionals based in India who may be savvy with respect to internet use. Future work may evaluate whether the pattern of results that the authors report for normative behavior does hold across other types of normative behavior.
Practical implications
These findings hint at a gap between the moral compass and the final “action” taken by DP users. What managers need to do is to create awareness among their customers about the implementation of DP/GIT and help users engage in normative behavior.
Originality/value
This research contributes to the literature by integrating the UTAUT and the NAM to explain normative behavior of IT use. The authors propose and test a model that identifies cognitive as well as social-psychological motivations to explain normative behavior in IT use, which have been sparingly studied in extant literature, and provides a holistic understanding of the phenomenon. As such, this research contributes to the existing knowledge of understanding of normative IT behavior.
Showing posts with label structural_equation_modelling. Show all posts
Showing posts with label structural_equation_modelling. Show all posts
Monday, 25 February 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.
Sunday, 17 June 2018
Student psychological distress and degree dropout or completion: a discrete-time, competing risks survival analysis
an article by Stefan Cvetkovski, Anthony F. Jorm and Andrew J. Mackinnon (University of Melbourne, Victoria, Australia) published in Higher Education Research & Development Volume 37 Issue 3 (2018)
Abstract
Studies of psychological distress (PD) in university students have shown that they have high prevalence rates. These findings have raised concerns that PD may be leading to poorer student outcomes, such as elevated dropout rates.
The aim of this study was to examine the association of PD in undergraduate university students with the competing risks of degree dropout or completion. It analysed data from the Household Income and Labour Dynamics in Australia (HILDA) survey.
The sample comprised 1265 university students. PD (i.e., probable depression and/or anxiety) was measured with a validated cut-off score of ≤65 on the 5-item Mental Health Inventory (MHI-5) from the Short Form 36 (SF-36). The study used an accelerated longitudinal design with student year of study as the metric of time and estimated dynamic discrete-time, competing risks survival models.
Contrary to expectations, the study found that students with PD had lower odds of degree dropout and higher odds of degree completion than students without PD in year 4 of their degrees.
This study contributes to the empirical literature on university student mental health by showing that, while PD can be debilitating and negatively affect students’ general educational experience, it is not as harmful to academic progress as might be assumed.
Abstract
Studies of psychological distress (PD) in university students have shown that they have high prevalence rates. These findings have raised concerns that PD may be leading to poorer student outcomes, such as elevated dropout rates.
The aim of this study was to examine the association of PD in undergraduate university students with the competing risks of degree dropout or completion. It analysed data from the Household Income and Labour Dynamics in Australia (HILDA) survey.
The sample comprised 1265 university students. PD (i.e., probable depression and/or anxiety) was measured with a validated cut-off score of ≤65 on the 5-item Mental Health Inventory (MHI-5) from the Short Form 36 (SF-36). The study used an accelerated longitudinal design with student year of study as the metric of time and estimated dynamic discrete-time, competing risks survival models.
Contrary to expectations, the study found that students with PD had lower odds of degree dropout and higher odds of degree completion than students without PD in year 4 of their degrees.
This study contributes to the empirical literature on university student mental health by showing that, while PD can be debilitating and negatively affect students’ general educational experience, it is not as harmful to academic progress as might be assumed.
Wednesday, 21 February 2018
Do environmental concerns affect commuting choices?: hybrid choice modelling with household survey data
an article by Jennifer Roberts and Gurleen Popli (University of Sheffield, UK) and Rosemary J. Harris (Queen Mary University of London, UK) published in Journal of the Royal Statistical Society: Series A (Statistics in Society) Volume 181 Issue 1 (January 2018)
Summary
To meet ambitious climate change goals governments must encourage behavioural change alongside technological progress. Designing effective policy requires a thorough understanding of the factors that drive behaviours.
In an effort to understand the role of environmental attitudes better we estimate a hybrid choice model (HCM) for commuting mode choice by using a large household survey data set. HCMs combine traditional discrete choice models with a structural equation model to integrate latent variables, such as attitudes, into the choice process.
To date HCMs have utilized small bespoke data sets, beset with problems of selection and limited generalizability. To overcome these problems we demonstrate the feasibility of using this valuable modelling approach with nationally representative data.
Our results suggest that environmental attitudes have an important influence on commute mode choice, and this can be exploited by governments looking to add to their climate change policy toolbox in an effort to change travel behaviours.
Full text (PDF 22pp)
I am too far away from using statistical information for this type of analysis but ignoring the bits of this article that I no longer understand it makes a great deal of sense.
Summary
To meet ambitious climate change goals governments must encourage behavioural change alongside technological progress. Designing effective policy requires a thorough understanding of the factors that drive behaviours.
In an effort to understand the role of environmental attitudes better we estimate a hybrid choice model (HCM) for commuting mode choice by using a large household survey data set. HCMs combine traditional discrete choice models with a structural equation model to integrate latent variables, such as attitudes, into the choice process.
To date HCMs have utilized small bespoke data sets, beset with problems of selection and limited generalizability. To overcome these problems we demonstrate the feasibility of using this valuable modelling approach with nationally representative data.
Our results suggest that environmental attitudes have an important influence on commute mode choice, and this can be exploited by governments looking to add to their climate change policy toolbox in an effort to change travel behaviours.
Full text (PDF 22pp)
I am too far away from using statistical information for this type of analysis but ignoring the bits of this article that I no longer understand it makes a great deal of sense.
Monday, 29 April 2013
The effects of classroom teaching on students' self-efficacy for personal development
an article by Derek Cheung and Edith Lai (,The Chinese University of Hong Kong, Shatin) published in British Journal of Guidance and Counselling Volume 41 Number 2 (April 2013)
Abstract
The personal development of students is an essential component of school guidance and counselling programmes, but no published research on guidance and counselling has investigated the effects of regular classroom teaching on students’ self-efficacy for personal development.
In this study, questionnaire items were constructed to measure classroom teaching, student self-efficacy for personal development and student use of deep learning strategies. Data were collected from 16,208 secondary school students in Hong Kong. Using structural equation modelling, regular classroom teaching was found to have a direct effect on personal development self-efficacy as well as an indirect effect through student use of deep learning strategies.
Implications of these findings for implementing a whole-school approach to guidance and counselling are discussed.
Abstract
The personal development of students is an essential component of school guidance and counselling programmes, but no published research on guidance and counselling has investigated the effects of regular classroom teaching on students’ self-efficacy for personal development.
In this study, questionnaire items were constructed to measure classroom teaching, student self-efficacy for personal development and student use of deep learning strategies. Data were collected from 16,208 secondary school students in Hong Kong. Using structural equation modelling, regular classroom teaching was found to have a direct effect on personal development self-efficacy as well as an indirect effect through student use of deep learning strategies.
Implications of these findings for implementing a whole-school approach to guidance and counselling are discussed.
Thursday, 20 December 2012
Employee Misuse of Information Technology Resources: Testing a Contemporary Deterrence Model
an article by John D'Arcy (University of Delaware, Newark, USA) and Sarv Devaraj (University of Notre Dame, USA) published in Decision Sciences
Volume 43 Issue 6 (December 2012)
Abstract
Recent research in information systems and operations management has considered the positive impacts of information technology (IT).
However, an undesirable side effect of firms’ increasing reliance on IT to support the distribution and delivery of goods and services to customers is a greater exposure to a diverse set of IT security risks. One such risk is intentional employee misuse of technology resources.
In this article, we draw upon modern deterrence frameworks to develop a predictive model of technology misuse intention that incorporates formal and informal sanctions as well as employment context factors. The model specifies previously untested relationships between formal and informal sanctions, thereby providing fresh insight into the role of sanctions in deterring technology misuse in organisations.
Our results suggest that a predisposition toward the need for social approval and moral beliefs regarding the behaviour are key determinants of technology misuse. Contrary to criminological research that has questioned the relative importance of formal sanctions in the deterrence process, we also found that the threat of formal sanctions has both direct and indirect influences on technology misuse intention.
Further, from an employment context standpoint, employees who spend more working days away from the office (i.e., “virtual” mode) appear more inclined to misuse their organization’s technology resources. The findings have implications for the research and practice of technology management.
Abstract
Recent research in information systems and operations management has considered the positive impacts of information technology (IT).
However, an undesirable side effect of firms’ increasing reliance on IT to support the distribution and delivery of goods and services to customers is a greater exposure to a diverse set of IT security risks. One such risk is intentional employee misuse of technology resources.
In this article, we draw upon modern deterrence frameworks to develop a predictive model of technology misuse intention that incorporates formal and informal sanctions as well as employment context factors. The model specifies previously untested relationships between formal and informal sanctions, thereby providing fresh insight into the role of sanctions in deterring technology misuse in organisations.
Our results suggest that a predisposition toward the need for social approval and moral beliefs regarding the behaviour are key determinants of technology misuse. Contrary to criminological research that has questioned the relative importance of formal sanctions in the deterrence process, we also found that the threat of formal sanctions has both direct and indirect influences on technology misuse intention.
Further, from an employment context standpoint, employees who spend more working days away from the office (i.e., “virtual” mode) appear more inclined to misuse their organization’s technology resources. The findings have implications for the research and practice of technology management.
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