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Previous studies have shown that insiders pose risks to the security of organisations’ secret information. Information security policy (ISP) intentional violation can jeopardise organisations. For years, ISP violations persist despite organisations’ best attempts to tackle the problem through security, education, training and awareness (SETA) programs and technology solutions. Stopping hacking attempts e.g., phishing relies on personnel’s behaviour. Therefore, it is crucial to consider employee behaviour when designing strategies to protect sensitive data. In this case, organisations should also focus on improving employee behaviour on security and creating positive security perceptions. This paper investigates the role of psychological capital (PsyCap), punishment and organisational security resources in influencing employee behaviour and ultimately reducing ISP violations. The model of the proposed study has been modified to investigate the connection between self-efficacy, resilience, optimism, hope, perceived sanction severity, perceived sanction certainty, security response effectiveness, security competence and ISP violation. The sample of the study includes 364 bank employees in Jordan who participated in a survey using a self-administered questionnaire. The findings show that the proposed approach acquired an acceptable fit with the data and 17 of 25 hypotheses were confirmed to be correct. Furthermore, the variables self-efficacy, resilience, security response efficacy, and protection motivation directly influence ISP violations, while perceived sanction severity and optimism indirectly influence ISP violations through protection motivation. Additionally, hope, perceived sanction certainty, and security skills have no effect on ISP infractions that are statistically significant. Finally, self-efficacy, resiliency, optimism, hope, perceived severity of sanctions, perceived certainty of sanctions, perceived effectiveness of security responses, and security competence have a substantial influence on protection motivation.

The second-generation mobile instant messaging (SMIM) proliferates with various relationship management functions: group chats, audio/video chats, file sharing, real-time location sharing, and nonverbal graphics, such as emojis and stickers. This study integrates the important but often overlooked affordances theory into innovation diffusion and proposes an SMIM continuance intention model. SMIM is a social affordance platform for users to develop new friendships and maintain their relationships. Integrated diffusion of innovation and affordance theoretical frameworks, this study investigates the influence of four factors on the success of using SMIM apps to improve friendship development and relationship management. Data were collected from 231 participants using a survey questionnaire in a public university in Taiwan. The findings confirm the effects of friendship development and relationship maintenance on the intention of users to continue using SMIM apps. Implications for research and practice are discussed.

This study focuses on the adoption of Healthcare Information System (HIS) in India’s healthcare services, which has led to an increased use of HIS software for managing patient information in hospitals. The study aims to evaluate the factors that influence hospital workers’ satisfaction with HIS usage and its impact on their intention to continue in the use of HIS. Primary data was collected through a survey questionnaire from 265 hospital workers. A new framework was developed, and Structural Equation Modeling (SEM) was used for analysis. Sensitivity analysis was also conducted on demographic data using an Artificial Neural Network (ANN) approach. The results indicated that all hypotheses were significant (p < 0.05). Effort expectancy was the most significant factor influencing hospital workers’ satisfaction (p < 0.01). Sensitivity analysis showed that education (Model-A) and experience in use of HIS (Model-B) were the most important factors. The study contributes by proposing a new theoretical framework and extending the previous research on HIS usage satisfaction. Overall, the study highlights the importance of easiness and usefulness in predicting HIS usage satisfaction.

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT’s early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users’ experiences.

The study is based on the technology-organization-environment (TOE) model which, attempted to determine the factors that are going to influence ICT adoption. The proposed research model evaluates the interplay among technological context (IT infrastructure, system security, and user capacity), organizational context (top management commitment, and innovations strategies), environmental context (quick response to the external agencies, interactive network infrastructure, and competitive pressure) and ICT adoption (productivity growth, organizational change, and competitiveness). Data were collected from 243 senior executives of full member firms of the Bangladesh Garments and Manufacturers Association (BGMEA) of examining the relationships among the constructs in the proposed framework utilizing structural equation modeling (SEM). The analysis of TOE factors revealed that environmental, organizational, and technological factors have a significant impact on the successful implementation of ICT tools. The study also discusses implications for management practitioners.

Smart speakers represent a growing product in home electronics. However, their capability to record voices in their immediate surroundings has spurred concerns about privacy violations. In this paper, we assess the extent of those concerns in the opinions of smart speaker users by examining the reviews posted by smart speaker users. We focus on South Korea as a representative of advanced Asian economies. The results show that Korean smart speaker users are either unconcerned or unaware of privacy issues, confirming the results of previous studies about UK users, but with an even lower degree of interest in the topic. However, for the few users concerned about privacy, their attitude towards privacy influences their overall opinion about smart speakers.

Corporate tax avoidance has been the subject of international debate since the Enron scandal and has raised awareness of the need for greater transparency in financial markets. Efforts have been made to strengthen financial reporting requirements and meet the needs of investors and other stakeholders, including digitalization of financial reporting through Extensible Business Reporting Language (XBRL). This study examines the impact of the mandatory adoption of XBRL on corporate tax avoidance. We tested our predictions using a panel dataset of Indonesian firms listed on the IDX stock exchange. Based on available information in the DATASTREAM database covering the 2013-2017 period, we used two proxies for tax avoidance i.e., GAAP effective tax rate and current effective tax rate. We estimated multiple regression model including industry and year fixed effects. The results show that XBRL implementation has reduced corporate tax avoidance. These findings suggest that improving corporate transparency through XBRL could play a deterrent tool to corporate tax avoidance. The results of this study should be useful to tax authorities and accounting standard setters supporting the benefits of digitalizing financial reporting and continuing to complete XBRL taxonomies around the world.

The objective of this study is to explore the perceptions of justice regarding the implementation of flexible work arrangements, as well as to analyze the effects of such arrangements on job satisfaction and organizational effectiveness. The present study posits three key aspects, namely distributive justice, procedural justice, and interactional justice, which are hypothesized to influence individuals’ impression of justice in relation to flexible work systems. To investigate the influence of job types on an R&D organization, specifically comparing R&D employees and office management employees, a dataset of 190 R&D employees and 50 office management employees was collected. The findings of the investigation provide empirical evidence that distributive justice has a significant impact on the level of job satisfaction among employees in both research and development (R&D) and office administration roles. Moreover, the influence of work satisfaction on organizational performance is noteworthy, particularly with regard to factors such as job dedication, organizational citizenship behavior, and knowledge sharing. The aforementioned findings offer significant insights for research and development (R&D) firms that have incorporated flexible work arrangements. These insights underscore the significance of emphasizing specific justice perceptions in order to augment job satisfaction and overall performance within the organization.

This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT “enjoyable” and “easy to use” and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.

The study aims to determine the impact of quality outcomes on behavior intentions in Financial Technology (FinTech) payment services. The study is focused on the development and testing of the impact of the SERVQUAL model on the TAM, i.e., Technology Acceptance Model for the measurement of the behavioral intention of users to use fintech payment services. The sample entails 578 specific survey responses from northern India from October to December 2022. The respondents were users of FinTech. The PLS-SEM technique was employed to explain the implementation process. Consequently, it discovered a significant relationship between the SERVQUAL models and the impact on behavioral intentions identified by TAM. The study will provide insight into the factors that impact the quality outcomes and adoption of Fintech payment services to the providers. The paper demystifies FinTech payment services in the range of perception of service quality outcomes and provides essential theories. The TAM model reflects the customer’s sense of satisfaction, usefulness, and attitude. In contrast, the SERVQUAL model demonstrates the user’s assessment of service quality outcomes such as quality, trust, security, and service quality positively affects behavioral intention in FinTech payment services.

Previous research has shown that employees tend to react more positively to corrective feedback from supervisors to the extent they perceive that they were treated with empathy, respect, and concern towards fair interpersonal treatment in receiving the feedback information. Then, to facilitate effective supervisory feedback and coaching, it would be useful for organizations to monitor the contents of feedback exchanges between supervisors and employees to make sure that supervisors are providing performance feedback using languages that are more likely to be perceived as interpersonally fair. Computer-aided text analysis holds potential as a useful tool that organizations can use to efficiently monitor the quality of the feedback messages that supervisors provide to their employees. In the current study, we applied computer-aided text analysis (using closed-vocabulary text analysis) and machine learning to examine the validity of language-based algorithms trained on supervisor language in performance feedback situations for predicting human ratings of feedback interpersonal fairness. Results showed that language-based algorithms predicted feedback interpersonal fairness with reasonable level of accuracy. Our findings provide supportive evidence for the promise of using employee language data for managing (and improving) performance management in organizations.

Management of the workforce in the early career stage who enter information security work after graduating from college or university so that they can continue to develop their information security careers without leaving the organization can be a solution to the problem of absolute shortage of staffing and lack of skills. This is because the workforce can improve their job skills, and organizations can build a stable, cost-effective human resource management system. This paper constructed and verified a turnover intention research model focusing on the factors that affect the turnover intention of early-stage workforce who took their first steps in society as an information security workforce after graduating from university or college; it confirmed that self-realization is a crucial factor. Furthermore, with in-depth interviews, the career path information of skilled workers, which is essential information necessary for self-realization, was analyzed, and the direction of HRM for self-realization of the workforce in the early career stage was presented.

Various corporates have launched products and brands to meet the diverse needs of consumers. However, an excess of information and products could be collapsed into a choice paradox far from the intention. As an alternative to these problems, curation-based services have recently been in the limelight and can be adopted into e-commerce sites. As one of the earlier studies on the considerable factors of curation services, this study focuses on the online fashion recommendation system in which design quality, interactivity, and perceived usefulness will affect trust, satisfaction, and continued intention to use. In the result, the design quality factor shows a positive effect on satisfaction, but not on the trust. Also, interactivity doesn’t demonstrate a significant positive effect on both the satisfaction and the trust factors far from the previous ones but the perceived usefulness had a positive effect on those. In addition, the personalization does not affect a significant effect on the satisfaction factor but on the trust factor. Subsequently, the trust affects the satisfaction, and the satisfaction on the continued intention to use factor, but trust does not significantly affect the continued intention to use directly.

This study explores how an organization has successfully implemented ML-supported HR services to resolve high employee turnover problems in the IT sector. The empirical setting of the research is where contradicting institutional logics exist among technical, HR, and business groups regarding the ML model development and use of the model predictions in HR services. Institutional framework is used to identify the roles of organizational actors and the legitimacy structures in the organizational environments that can shape or constrain the ML led organizational changes. In institutional theories, technology adoption and organizational change are not only constrained by organizational context, but also fostered through organizational actors’ roles and efforts to increase the legitimacy for the change. This research found that when multiple contradicting institutional logics exist, legitimizing the establishment of an enabling environment for multiple logics to reconcile and for the project to move forward is critical. Industry-wide conditions, previous experiences with the pilot ML project, forming a TFT with clearly defined roles and responsibilities, and relevant KPIs are found to legitimize the HR team and the business division to collaborate with the technical personnel to launch ML-supported HR services.