Innovation is the ultimate force that drives the development of society. In this dissertation, I examine the economic and organizational outcomes of technological innovations. In my first paper, I study how Artificial intelligence (AI) technology innovation replaces the intermediary role of real estate agents by reducing information asymmetry through delegation mechanisms. I found that consumers are more likely to delegate to AI algorithms as an alternative information source over real estate agents and this effect leads to the reduction of real estate agents’ employment. In my second paper, I studied technology innovation-led remote workforce settings from a cybersecurity risk perspective. Remote workforces are becoming more common due to technological advancements such as blockchain, and cybersecurity risks are documented to be higher for such remote workforces due to reduced monitoring and interactions with peers. I built and tested a model to explain cybersecurity behaviors in remote settings and found that determinants such as social influence differ from determinants in in-office settings. Both studies have implications for helping us better embrace the benefits of technology while controlling its negative effects.
Hebat Allah Adel, sayed abdelgaber, Wessam H. El-Behaidy
Ensuring transparency and security in digital recruitment systems remains a critical challenge. This study proposes BC-XAIA, a unified framework that integrates blockchain, smart contracts, explainable artificial intelligence (XAI), and agile methodology to enable consistent, secure, and traceable recruitment decision-making. Smart contracts, implemented in Solidity and deployed using the Remix Ethereum IDE, automate key processes such as identity verification, data access control, and behavior monitoring, reducing reliance on centralized intermediaries. To support intelligent decision-making, multiple machine learning models, including Random Forest, Logistic Regression, and Support Vector Machine (SVM), were trained and evaluated on a recruitment dataset, with Random Forest achieving the highest performance, reaching an accuracy of 93%. To enhance transparency, SHAP and LIME were employed to provide both global and local interpretability of model predictions. Furthermore, agile methodology is embedded to drive continuous adaptation, iterative development, and stakeholder feedback throughout the recruitment lifecycle. Unlike existing recruitment systems that treat blockchain, AI, and explainability separately, BC-XAIA unifies these technologies within an agile and decentralized architecture. Overall, BC-XAIA establishes a secure, transparent, and explainable decentralized recruitment ecosystem that enhances trust, fairness, and intelligent decision-making in next-generation HR systems.
The rapid digital transformation has made verifiable professional digital skills essential for workforce competitiveness, yet traditional resumes and certificates suffer from high fraud rates (50–70%), lengthy manual verification, and failure to recognize non-traditional pathways. This paper investigates SSI-, DID-, and W3C VC-based digital skills wallets as a solution to restore cryptographic trust in HR recruitment. Adopting the Design Science Research Methodology (DSRM), we conducted a PRISMA 2020 systematic review of 42 high-quality sources (2022-early 2026). The review established the technical maturity of SSI/VC technologies for micro-credentials and Learning and Employment Records (LERs) while revealing critical gaps in enterprise HR integration and emerging-market (particularly China) applications. We designed a modular, blockchain-optional digital skills wallet architecture fully compliant with W3C Verifiable Credentials Data Model v2.0, 1EdTech Comprehensive Learner Record, and China’s RealDID national identity infrastructure. The artifact supports lifelong credential aggregation, selective disclosure via BBS+ zero-knowledge proofs, and instant cryptographic verification (<3 seconds). The design was demonstrated through three China-specific recruitment use cases and empirically validated via a mixed-methods survey with 42 HR professionals and recruiters from major technology companies in Beijing, Shanghai, Shenzhen, and Guangzhou. Results indicated strong perceived utility: credential fraud was rated a major issue (M = 4.69), the wallet was expected to substantially reduce verification time (M = 4.57) and increase confidence in candidate claims (M = 4.45), with positive willingness to pilot or adopt (M = 4.19), especially when integrated with RealDID. These findings demonstrate that SSI-based digital skills wallets can near-eliminate resume fraud, collapse verification from weeks to seconds, expand talent pools through skills-first matching, and ensure privacy-preserving selective disclosure while aligning with national digital identity strategies. The study contributes a replicable DSRM template bridging verifiable credentials and skills-based talent management literatures, together with practical recommendations for HR leaders, ATS integration, and policy development.
Distributed recruitment is changing the way companies hire people and is also creating new problems for Human Resources teams. It is now much easier for people to fake documents, pretend to be someone else, or carry out employment fraud, while old methods like manual checks, emails, and database queries cannot keep up with tricks such as fake videos or forged papers. SafeHire is designed to solve these problems as a system that checks if people are who they claim to be and fits modern hiring needs. Instead of slow and easily fooled methods, it uses Zero-Knowledge Proofs with the Anon-Aadhaar protocol so people can prove their identity without sharing private information. Government IDs are verified offline using XML signature validation, and academic records are stored securely using SHA-256 hashing so they cannot be changed. To check documents, SafeHire uses Jaro-Winkler and Levenshtein distance methods to find small errors and also verifies employers using Corporate Identification Numbers (CIN). All data is protected so only the right people can access it through strict access rules. SafeHire is a faster and more secure way to hire, using system-based verification connected to trusted records to reduce the weaknesses of older applicant tracking systems and make hiring more reliable.
D. Hema Lakshmi, B. Prem Sai Siddhik, B. Akhil Kumar, Ch. Siva Venkata Sai Tharun · 5 authors
Resumes are a key part of traditional hiring, but when human reviewers may not accurately identify the true skills of candidates. Sometimes, when checks are done, fraudulent credentials may pass undetected due to limitations in manual verification. A new method is presented here that uses smart algorithms in a distributed ledger system. By connecting machine learning with secure data records, trust in verifying applicants grows a lot. The proposed system improves efficiency by reducing reliance on traditional keyword-based filtering. The software uses natural language tools to look at the applicant's information, extracts relevant skills and generates a performance score for each candidate. Cryptographic hashes of credentials are stored on a distributed ledger, ensuring that validation cannot be altered or hacked. An online model was created using ReactJS, Flask, MongoDB, and connections to the Ethereum Blockchain. The results show that the method automatically sorts job applicants, quickly checks their documents, and consistently finds qualified people in different fields. Combining smart algorithms with decentralised records increases trust, cuts down on manual tasks, and brings more clarity to the hiring process.
Utilizing information technology (IT) in human resource management (HRM) platforms is a prerequisite for every business to successfully adopt and implement the Fourth Industrial Revolution (Industry 4.0). These methods are necessary to provide a fair, efficient, transparent, and safe environment. Successful implementation of these requirements may be facilitated by blockchain technology, which is based on a decentralized distributed ledger. The purpose of this study is to ascertain how blockchain technology is currently being applied in human resource management. Along with anticipated adoption barriers that can restrict its use, it also outlines possible opportunities associated with the implementation of blockchain technology in the field of human resource management. There are definite benefits when comparing the proposed system to the existing hiring practices. Thus, blockchain technology has also been widely used in human resources management. This essay will look more closely at and explore blockchain technology's application potential in HRM. To determine the possible opportunities associated with the use of blockchain technology in the HRM domain as well as the expected adoption challenges that may impede its utilization, this paper analyses the findings of an empirical study that conducted one semi-structured interview with HRM experts. Both blockchain and HRM researchers can benefit from the study by using the potential suggested as a basis for future research and attempting to address the expected adoption issues. KEY WORDS: Blockchain Technology, Human Resource Management (HRM), Industry 4.0, Decentralized Ledger, Recruitment and Hiring, Adoption Challenges.
This study aims to understand better how blockchain-integrated HR analytics may improve staff management practices in businesses. The study's primary goals are to determine how blockchain technology affects HR procedures, analyze its effects on worker performance, and determine how policies will be affected by its adoption. The paper examines the incorporation of blockchain technology into HR analytics by synthesizing case studies, industry reports, and current literature through a secondary data-based review technique. The main conclusions are improved data security and integrity, streamlined ingenious contract procedures, open decision-making, performance management based on data, and encouraging employee accountability and ownership. Addressing technological complexity, regulatory obstacles, interoperability problems, energy consumption issues, and data access and control problems are some policy consequences. To leverage the benefits of blockchain technology in HRM, policymakers are advised to provide clear regulatory frameworks, invest in technical support and training, and investigate long-term, privacy-preserving solutions. Blockchain-integrated HR analytics present a viable way for businesses to enhance staff management plans and promote organizational efficacy in the digital age.
Candy So Suk Yi, Eric Yung, Christopher Fong, Shilpi Tripathi
Globalization brings advantages to worldwide awareness and cross-border technology dissemination in two respects to enable nations to readily access foreign expertise and enhance international competition from the increase of emerging market companies, as well as innovation and the introduction of foreign innovations (Aslam et al., 2018). Human Resources (HR) nowadays generally faces various difficulties in the world internet era and spends a lot of time connecting, screening, and verifying the resume of applicants, conducting credentials verifications, and checking backgrounds to reduce the likelihood of poor recruitment. For example, recruiters connect the profile of candidates from different channels such as direct application, recruitment agency, and social media; and hiring resume verifications is therefore a bottleneck. Hong Kong's telecommunications industry is totally privately-owned and faces no restriction on foreign investment, and it is also open for competition. Use of blockchain in the twenty-first for the period from 2004 to 2014, an instance of international expertise and technology will increase innovation ability and labour productivity development. Experts say that obtaining verification of credentials using blockchain can reduce costs and delays, increase confidence and increase hiring automation (Han, 2017). Background checks on shortlisted candidates / applicants’ lies are used to find increasing numbers of companies on their profiles to get job opportunities (Wood et al., 2007 cited in Brody, Richard G, 2010).