Search results

Increasing incidents of privacy invasion on social networking sites (SNS) are intensifying the concerns among stakeholders about the misuse of personal data. However, there seems to be limited research on exploring the impact of specific privacy concerns on users’ intention to engage in various privacy protection behaviors. This study aims to examine the role of social privacy concerns, institutional privacy concerns and privacy self-efficacy as antecedents of privacy protection–related control activities intention among young adults active on SNS.

Data collected from 284 young adults active on SNS was analyzed through partial least squares structural equation modeling using Smart PLS.

The results indicate that institutional privacy concerns, social privacy concerns and privacy self-efficacy positively influence the control activities intention of SNS users. The extent of privacy self-efficacy and privacy protection-related control activities intention differs among users based on gender.

This study is limited to a population of young adults in the age group of 18–25 years.

The findings of this study form the basis for specific recommendations addressing the different types of privacy concerns experienced by social media users, promoting responsible privacy control behaviors on online platforms and discouraging the possible misuse of information by third parties.

This study validates a theoretical framework that can contribute to future investigations concerning the use of SNS. The study findings form the basis for a set of practical recommendations for policymakers, SNS platforms and users.

The present study aims to assess the impact of narcissism, self-confidence and auditor's characteristics on audit report readability for companies listed on the Tehran Stock Exchange.

The study’s statistical population comprises firms listed on the Tehran Stock Exchange. The present research used a systematic elimination method, and 1,162 firm-year observations were obtained for seven years from 2012 to 2018. Three variables including auditor tenure, audit fee and audit specialization are used for measuring auditing features. The Fog index is used as a proxy for measuring audit report readability. In addition, in this paper, four regressions, including fixed effects, random effects, pooled and T+1, are used to estimate reliable coefficients.

The findings show a negative and significant relationship between auditor’s characteristics (tenure, fee and specialization) and audit report readability. Moreover, the variables of the auditor’s narcissism, self-confidence and mandatory auditor change have a positive and significant association with audit report readability. This study lends support to the theories of personality disorder and behavioral decision.

Since narcissism and self-confidence are two characteristics that shape an individual’s character and personality, some involved behavioral factors in auditors’ characteristics contribute to their decisions. The effects of these should be detected to enhance the decision-making process. The said factors significantly impact audit report readability. Hence, this paper attempts to assess the effect of the said factors on audit report readability.

The potential applications of information and communication technologies in the workplace are wide-ranging and, especially since the COVID-19 pandemic, have increasingly found their way into the field of electronic performance monitoring (EPM) of employees. This study aims to examine the influence of EPM on individual performance considering the aspects of privacy invasion, organizational trust and individual stress within an organization. Thus, important insights are generated for academia as well as business.

A theoretical framework was developed which conceptualizes perceived EPM as independent variable and individual performance as dependent variable. Moreover, the framework conceptualizes three mediator variables (privacy invasion, organizational trust and individual stress). Based on a large-scale survey (N = 1,119), nine hypotheses were tested that were derived from the developed framework.

The results indicate that perception of EPM significantly increases privacy invasion, reduces organizational trust, increases individual stress and ultimately reduces individual performance. Moreover, it was found that privacy invasion reduces organizational trust and that this lowered trust increases individual stress. Altogether, these findings suggest that the use of EPM by employers may be associated with significant negative consequences.

This research enriches the literature on digital transformation, as well as human–machine interaction, by adopting a multidimensional theoretical and empirical perspective regarding EPM in the workplace context, in which the influence of EPM perceptions on individual performance is examined under the influence of different aspects (privacy invasion, organizational trust and individual stress) not currently considered in this combination in the literature.

Cybersecurity attacks on critical infrastructures, businesses and nations are rising and have reached the interest of mainstream media and the public’s consciousness. Despite this increased awareness, humans are still considered the weakest link in the defense against an unknown attacker. Whatever the reason, naïve-, unintentional- or intentional behavior of a member of an organization, the result of an incident can have a considerable impact. A security policy with guidelines for best practices and rules should guide the behavior of the organization’s members. However, this is often not the case. This paper aims to provide answers to how cybersecurity-related behavior is assessed.

Research questions were formulated, and a systematic literature review (SLR) was performed by following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The SLR initially identified 2,153 articles, and the paper reviews and reports on 26 articles.

The assessment of cybersecurity-related behavior can be classified into three components, namely, data collection, measurement scale and analysis. The findings show that subjective measurements from self-assessment questionnaires are the most frequently used method. Measurement scales are often composed based on existing literature and adapted by the researchers. Partial least square analysis is the most frequently used analysis technique. Even though useful insight and noteworthy findings regarding possible differences between manager and employee behavior have appeared in some publications, conclusive answers to whether such differences exist cannot be drawn.

Research gaps have been identified, that indicate areas of interest for future work. These include the development and employment of methods for reducing subjectivity in the assessment of cybersecurity-related behavior.

To the best of the authors’ knowledge, this is the first SLR on how cybersecurity-related behavior can be assessed. The SLR analyzes relevant publications and identifies current practices as well as their shortcomings, and outlines gaps that future research may bridge.

This study aimed to identify and analyse the key factors influencing the adoption of e-government services and to discern their implications for various stakeholders, from policymakers to platform developers.

Through a comprehensive review of existing literature and detailed analysis of multiple studies, this research organised the influential factors based on their effect: highest, direct and indirect. The study also integrated findings to present a consolidated view of e-government adoption drivers.

The research found that users' behaviour, attitude, optimism bias and subjective norms significantly shape their approach to e-government platforms. Trust in e-Government (TEG) emerged as a critical determinant, with security perceptions being of paramount importance. Additionally, non-technical factors, such as cultural, religious and social influences, play a substantial role in e-government adoption decisions. The study also highlighted the importance of performance expectancy, effect expectancy and other determinants influencing e-government adoption.

While numerous studies have explored e-government adoption, this research offers a novel classification based on the relative effects of each determinant. Integrating findings from diverse studies and emphasising non-technical factors introduce an interdisciplinary approach, bridging the gap between information technology and fields like sociology, anthropology and behavioural sciences. This integrative lens provides a fresh perspective on the topic, encouraging more holistic strategies for enhancing e-government adoption globally.

The purpose of this study is to investigate artificial intelligence (AI) as enabler of future library services, with consideration to how prepared are librarians in African university libraries.

This study applied the interpretive content/document analysis of literature harvested from different databases of Scopus and Web of Science. AI could be used to perform daily routines in circulation, serial, reference and selective dissemination of information among others. It could also be applied to the provision of innovative services of recognition of library activities such as answering research quarries, cataloguing and classification of library materials and management of library system software of different databases within the library systems.

It could be deduced from the study that AI would continue to serve as a panacea to future library services irrespective of its geographical context. Due to the evolving nature of knowledge growth, AI having its roots in the field of engineering has been found useful to support future library services. The support accrued from library service delivery in the library profession has made librarians continue to interact with other intelligent machines that can demonstrate human behaviour even though they are not real human beings. The behaviour of machines and AI where human beings play a significant role has brought many renovations in the management of complex tasks of processing, communication, knowledge representation, decision making and suggestions, on potentials of diverse work operations.

The understanding that the present paper portrays in the context of future library services is that there is no way the AI could function without a human interaction perspective when drawing an analogy from computer science, information science and information systems fields of study.

The interest of users across their background would be strengthen if AI advances transformed the handling complex tasks of processing, communication, knowledge representation, decision-making and giving suggestions, among other things. The possibilities of diverse work operations from empirical evidence of studies consulted in recent times gave the authors the impetus to consider AI as the enabler of future library services.

The increasing demands from library patrons have prompted librarians to adapt their methods of delivering services. These emerging technologies have also brought about shifts in approaches to teaching and learning. Consequently, the recent surge in digital technology-driven service innovations has ushered in a fresh paradigm for education and research. In response to these changes, librarians are actively seeking novel and innovative technologies to enhance user experiences within their libraries. They serve as catalysts for introducing modern and advanced technologies, consistently adapting to contemporary tools that enhance their offerings.

The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use them.

The authors apply a structural equation modelling (SEM) approach to test the research hypotheses through data coming from a structured questionnaire.

The results show that the higher the importance attributed to usefulness and ease of use, the higher the positive attitude that in turn positively affects the intention to use smart speakers. A significant relationship also emerged between task technology fit and attitude towards smart speakers, as well as between perceived enjoyment and attitude towards smart speakers. Perceived privacy risk, innovativeness and social attraction have been found to not significantly impact attitudes towards smart speakers.

Although several academic studies have focused on various aspects of smart technologies, only a few studies discuss the factors that push consumers to use smart speakers for activities related to commercial transactions. Therefore, looking at the rapid rise of smart speakers for daily tasks and the gradual acceptance of voice interaction with digital tools, the authors proposed a study about Italian users' intention to use smart speakers. Specifically, to fill the gap in the existing literature, the authors applied a SEM approach to identify utilitarian and hedonic benefits that motivate the use of these devices.

Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by exploring teachers' perspectives on the adoption of ChatGPT, with a focus on identifying factors that motivate and inhibit them to adopt ChatGPT for educational purposes.

This research has employed a interpretative phenomenological analysis (IPA) qualitative approach. Through in-depth interviews among the teachers, data will be collected to identify the motivating and inhibiting factors that impact teachers' willingness to adopt ChatGPT. The data was collected from 34 teachers working across 10 branches of the University of Technology and Applied Sciences (UTAS) in Oman.

The analysis revealed four themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purpose. These include Theme 1: Exploration of innovative education technologies, Theme 2: Personalization teaching and learning, Theme 3: Time-saving and Theme 4: Professional development. On the other hand, inhibiting factors includes five themes which includes Theme 1: Reliability and accuracy concerns, Theme 2: Reduced human interaction, Theme 3: Privacy and data security, Theme 4: lack of institutional support and Theme 5: Overreliance on ChatGPT.

This study contributes to the understanding of teachers' perspectives on the adoption of ChatGPT in education. By understanding teachers' perspectives, policymakers can design appropriate policies and service providers can customize their offerings to meet teachers' requirements. The study's findings will be valuable for higher education institutions (HEIs) in formulating policies to ensure the appropriate and effective utilization of ChatGPT. The study will provide suggestions to ChatGPT service providers, enabling them to focus on motivating factors and address inhibiting factors, thereby facilitating the seamless adoption of ChatGPT among teachers.

In comparison to previous studies, this study goes beyond merely discussing the possible benefits and limitations of ChatGPT in education. This research significantly contributes to the understanding of ChatGPT adoption among teachers by identifying specific motivating and inhibiting factors that influence teachers to adopt ChatGPT for educational purposes. The research enables to gain important new insights that were not previously found, giving a fresh dimension to the existing literature.

This study aims to understand consumer behaviour in the context of online food delivery (OFD), especially given the mandatory lockdown imposed in some countries that have modified the behaviour of consumers. Using model goal-directed behaviour (MGB), this study was conducted to investigate consumer perceived risk on the use of OFD services.

Responses of food delivery services users were collected online throughout April 2020 to understand their risk profile and behaviour. A total of 339 responses were collected and subsequently analysed using partial least square (PLS). Both measurement and structural model were evaluated to ensure that the structural equation modelling (SEM) is valid.

The results revealed that attitude (ATT), subjective norm (SN), positive anticipated emotion (PAE) and negative anticipated emotion (NAE) and perceived behavioural control (PBC) significantly influenced users' desire. It was also found that PBC significantly influenced users' intention. The empirical result suggests that performance, privacy, financial, physical and the risk of contracting COVID-19 negatively influenced users' desire. In contrast, only physical and the risk of contracting COVID-19 negatively influenced users' intention to use OFD services.

These findings provide OFD service providers and scholars with significant insights into what compels urbanites to adopt OFD services amid a health pandemic. It also allows OFD companies to realign their operation in addressing these concerns and changes in consumer behaviour.

Against the backdrop of the pandemic, this study provides insights for OFD providers in developing new strategies and approaches for business development and consumer retention in a post-pandemic world.

本研究擬瞭解與網上訂餐相關的消費行為；尤其當有些國家推行了改變消費者行為的強制性封鎖政策的情況下，這類研究更具意義。透過應用目標導向行為模型，本研究擬探討消費者在使用網上訂餐服務時所意識到的風險。

研究人員於 2020年4月網上收集使用訂餐服務人士的意見，以瞭解其風險狀況和行為。研究共收集了339位人士的意見，並以偏最小二乘法進行分析。測量和結構模型均加以評估，以確保結構方程模型是站得住腳的。

研究結果顯示，態度、主觀規範、預期的正面和負面情緒、以及感知的行為控制，顯著地影響了用戶的慾望。研究結果亦發現，感知的行為控制顯著地影響了用戶的意圖。研究的經驗性結果暗示了表現、私隱、金錢上的爭議、可能會導致的身體損傷和感染2019冠狀病毒病的風險，負面地影響用戶的慾望。相比之下，影響著用戶使用網上訂餐服務的意圖的因素就只有可能會導致的身體損傷和感染2019冠狀病毒病的風險。

研究的結果，為提供網上訂餐服務的營運者和研究學者提供了重要的啟示，使他們更瞭解是什麼因素會迫使都市人在與健康息息相關的大流行病期間使用網上訂餐服務。而且，提供網上訂餐服務的公司亦可藉此重新調整其營運，以能處理客戶的憂慮和應付消費行為的變化。

在大流行病肆虐的背景下，本研究為網上訂餐服務提供者給予了啟示，以便他們能在後疫情時代制定新的策略和營運方法，以拓展其業務和留住消費者。