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1 – 10 of over 2000Botong Xue, Feng Xu, Xin Luo and Merrill Warkentin
A growing number of studies have investigated the effect of ethical leadership on behavioral outcome of employees. However, considering the important role of ethics in IS…
Abstract
Purpose
A growing number of studies have investigated the effect of ethical leadership on behavioral outcome of employees. However, considering the important role of ethics in IS security, the security literature lacks a theoretical and empirical investigation of the relationship between ethical leadership and employees' security behavior, such as information security policy (ISP) violation. Drawing on social learning and social exchange theories, this paper empirically tests the impact of ethical leadership on employees' ISP violation intention through both information security climate (i.e. from a moral manager's perspective) and affective commitment (i.e. from a moral person's perspective).
Design/methodology/approach
The research was developed based on social learning theory and social exchange theory. To measure the variables in the model, the authors used and adapted measurement items from previous studies. The authors conducted a scenario-based survey with 339 valid responses to test and validate the research model.
Findings
Results indicated that information security climate fully mediates the relationship between ethical leadership and ISP violation intention. The authors also found that information security climate enhances the negative effect of affective commitment on ISP violation intention.
Originality/value
This research contributes to the literature of information security by introducing the role of ethical leadership and integrating two theories into our research model. This study also calls attention to how information security climate and affective commitment mediate the relationship between ethical leadership and employees' ISP violation intention. The theory-driven study provides important pragmatic guidance for enhancing the understanding of the importance of ethical leadership in information systems security research.
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Kenning Arlitsch, Jonathan Wheeler, Minh Thi Ngoc Pham and Nikolaus Nova Parulian
This study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional…
Abstract
Purpose
This study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional repositories (IR) as well as potential factors affecting their use, including repository size, platform, content, device and global location. The RAMP dataset is unique and public.
Design/methodology/approach
The webometrics methodology was followed to aggregate and analyze use and performance data from 35 institutional repositories in seven countries that were registered with the RAMP for a five-month period in 2019. The RAMP aggregates Google Search Console (GSC) data to show IR items that surfaced in search results from all Google properties.
Findings
The analyses demonstrate large performance variances across IR as well as low overall use. The findings also show that device use affects search behavior, that different content types such as electronic thesis and dissertation (ETD) may affect use and that searches originating in the Global South show much higher use of mobile devices than in the Global North.
Research limitations/implications
The RAMP relies on GSC as its sole data source, resulting in somewhat conservative overall numbers. However, the data are also expected to be as robot free as can be hoped.
Originality/value
This may be the first analysis of aggregate use and performance data derived from a global set of IR, using an openly published dataset. RAMP data offer significant research potential with regard to quantifying and characterizing variances in the discoverability and use of IR content.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0328
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Patrick OBrien, Kenning Arlitsch, Jeff Mixter, Jonathan Wheeler and Leila Belle Sterman
The purpose of this paper is to present data that begin to detail the deficiencies of log file analytics reporting methods that are commonly built into institutional repository…
Abstract
Purpose
The purpose of this paper is to present data that begin to detail the deficiencies of log file analytics reporting methods that are commonly built into institutional repository (IR) platforms. The authors propose a new method for collecting and reporting IR item download metrics. This paper introduces a web service prototype that captures activity that current analytics methods are likely to either miss or over-report.
Design/methodology/approach
Data were extracted from DSpace Solr logs of an IR and were cross-referenced with Google Analytics and Google Search Console data to directly compare Citable Content Downloads recorded by each method.
Findings
This study provides evidence that log file analytics data appear to grossly over-report due to traffic from robots that are difficult to identify and screen. The study also introduces a proof-of-concept prototype that makes the research method easily accessible to IR managers who seek accurate counts of Citable Content Downloads.
Research limitations/implications
The method described in this paper does not account for direct access to Citable Content Downloads that originate outside Google Search properties.
Originality/value
This paper proposes that IR managers adopt a new reporting framework that classifies IR page views and download activity into three categories that communicate metrics about user activity related to the research process. It also proposes that IR managers rely on a hybrid of existing Google Services to improve reporting of Citable Content Downloads and offers a prototype web service where IR managers can test results for their repositories.
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Soumi Roy Chowdhury, Alok K. Bohara and Jeffrey Drope
The purpose of the study is to assess the differential impact of gender and cancer sites on mental burden across different types of cancer and control patients.
Abstract
Purpose
The purpose of the study is to assess the differential impact of gender and cancer sites on mental burden across different types of cancer and control patients.
Design/methodology/approach
The paper is based on a primary survey undertaken in 2015–2016 of 600 cancer and 200 control patients across five hospitals of Nepal. The data was analyzed using propensity score matching methods and treatment effect weighting estimators.
Findings
The authors find that of all the types of patients covered under this study, cervical cancer patients suffered from a greater intensity of anxiety and lack of functional wellbeing. On an average, all other female, male cancer patients, and control patients experience significantly lower intensity of mental burden in the range of 1.83, 2.63 and 3.31, respectively when compared to patients of cervical cancer. The results are robust across all the four treatment effect estimators and through all the measures of mental burden. The implications of suffering from cervical cancer, as a unique gynecological cancer was studied in-depth. An effect size analysis pointed out to the dysfunctional familial relationship as additional causes of concern for cervical cancer patients.
Originality/value
An important finding that emerged is that female cancer patients especially those who have cervical cancer should be given special attention because they appear to be the most vulnerable group. Further work is needed to delineate the reasons behind a cervical cancer patient facing higher amount of stress.
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