Business Department

جوامع همگون به زودي به صورت نمادهايي از دوران گذشته درآمده و به تاريخ خواهند پيوست. مهاجرت مستمر، برقراري ارتباط تنگاتنگ بين فرهنگ هاي گوناگون، انعقاد توافق نامه هاي بين المللي، تاسيس شركت هاي فرامليتي و تشكيل اتحاديه هاي متشكل از فرهنگ هاي گوناگون همگي شاهدي بر اين مدعاست كه وارد عصر تنوع شده ايم. مقاله حاضر حاصل تحقيق انجام شده در دانشگاه آكسفورد انگلستان و در مورد رابطه بين بكار گيري نيروي كار متنوع و اصول عدل و انصاف است. نويسنده با نگاهي اصولي به مفهوم تنوع و انواع آن، به معرفي مشكلات مديريت نيروي كار متنوع از ديدگاه اجتماعي، فرهنگي و قانوني پرداخته و با ذكر نمونه هايي از اين چالش ها در سيستم مديريتي كشور انگلستان، توجه مديران كشور را به چاره جويي در اين باره جلب مي كند. در پايان نيز مطالعه موردي از سازمان آكسفام، سومين سازمان بزرگ خيريه در جهان، ارائه شده است.

کليدواژگان: اصل تنوع، تنوع در نيروي كاري، انصاف، عدل، تبعيض، انتخاب و بكارگيري نيروهاي متنوع، آكسفام (مطالعه موردي)

Purpose Building on consumer socialization theory, the purpose of this paper is to examine antecedents and consequences of generating and sharing brand-related content on social media in a restaurant context. Design/methodology/approach A scale development process was undertaken to develop the scale for brand-related user-generated content (BRUGC). Then the authors tested the antecedents and consequences of BRUGC using 375 responses obtained through a mall-intercept survey. The hypotheses were tested using structural equation modeling with AMOS. Findings Study findings revealed that age, time on Facebook, number of Facebook friends, Facebook usage intensity, and need for self-enhancement were key antecedents of both the generation and sharing of BRUGC. The results also indicated that gender, race and need for self-affirmation were not significantly related to generating and sharing BRUGC. Both generating and sharing BRUGC were positively associated with attitude and intentions towar...

Quantum key distribution or QKD is a concept which utilizes the properties of quantum mechanics to establish an effective way of decrypting keys without compromising them as happens with the traditional cryptography (Bennett, 1993). Conventional cryptography techniques employ the mathematical problems with high computation complexity; yet they are not resistant to the attacks by enhancing classical and even quantum computers (Ekert, 1991). On the other hand, QKD takes advantage of the versatile quantum particles like the super particles and the entangled particles, whereby any try to try to intercept the key exchange process will always affect the quantum states of the particles, thereby making the intruder known (Brassard, 1984).
This paper aims at discussing the theoretical frameworks of QKD with reference to the fact that the technology can only be intercepted en-route while it provides the end-to-end security assurances that cannot be breached (Ekert, 1991). Specifically, we explore two major QKD protocols: The two popular quantum protocols are BB84 that encodes and transmit information using the polarization of photons (Brassard, 1984); E91, which generates and distributes cryptographic keys utilizing quantum entanglement (Ekert, 1991). The deployment of these protocols shows the contribution of QKD in the detection of eavesdropping attempts thereby providing immense security in its communication (Bennett, 1993).

This study investigated the role of District Security Committees in the oversight of private security companies in Uganda to contribute to ways through which private public security provision can be enhanced for sustainable security and development. Using Wakiso and Kampala as case studies, the study relied on a qualitative approach based on key informant in-depth interviews involving members of District Security Committees, private security company supervisors, supervisors at police headquarters in charge of private security organization and private security services contractors and members to analyze the mechanisms and challenges District Security Committees face in the oversight of private security companies.

In today's fast-paced digital age, data centers play a crucial role in supporting essential internet operations such as cloud computing, artificial intelligence (AI), and machine learning (ML). As these technologies become more complex and widespread, the need for faster, more efficient, and environmentally sustainable digital infrastructures grows. It's increasingly important to incorporate advanced optical network technologies early in data center projects. Data center interconnects turned to optical technologies almost a decade ago, and the recent acceleration in data center requirements is expected to further drive fiber optic technologies deeper into the systems architecture. This paper analyses the role of advanced fiber optic technologies in the revolutionary journey of U.S. Data Centers and Technologies. It critically studies the existing data center infrastructure to unearth the challenges and opportunities and proposes the use of advanced fiber optic technologies in data centers to increase efficiency, security and sustainability which is a critical issue for investors. The proposition is in line with the US national interest by expanding and securing the data infrastructure thereby bolstering economic growth through the creation of skilled job opportunities fostering a robust labor market in telecommunications and maintaining the US as a leader in technological advancements.

The United States faces an escalating array of public safety challenges, from violent crime and mass shootings to increasingly severe climate-related disasters. Between 1980 and 2024, the U.S. experienced 387 weather and climate disasters, each with damages surpassing $1 billion, amounting to over $2.74 trillion in costs. Similarly, mass shootings and gun violence reached an alarming frequency, with more than 630 mass shooting incidents recorded by the Gun Violence Archive (GVA) in 2023 alone. The National Interagency Fire Center (NIFC) also reported 56,580 wildfires that burned over 2.7 million acres nationwide in the same year. These figures highlight the pressing need for robust, realtime public safety and emergency management systems to better predict, respond to, and mitigate such incidents. This paper explores the transformative potential of Artificial Intelligence (AI) in enhancing public safety and emergency management in the U.S. By leveraging AI-driven predictive analytics, machine learning (ML) models, and advanced threat detection algorithms, this study proposes an integrated approach to optimizing crime prevention, disaster response, and public safety operations. The research builds upon recent advancements in predictive analytics, deep learning, and cybersecurity measures. Through the analysis of real-time data from crime statistics, social media, IoT sensors, and environmental conditions, this study aims to demonstrate how AI can reduce response times, anticipate public safety threats, and allocate resources more effectively. The study will present case studies on the practical application of AI in real-time crime prediction, disaster management, and threat detection, showcasing how law enforcement, emergency management, and cybersecurity teams can use AI to shift from reactive responses to proactive, intelligence-driven operations. Moreover, it will address ethical concerns around AI deployment in public safety, such as privacy, algorithmic bias, and data governance, proposing frameworks for ensuring responsible use of these technologies. The ultimate goal is to offer a strategic roadmap for integrating AI into U.S. public safety infrastructure, enhancing preparedness, and protecting communities from the growing risks of violent crime, natural disasters, and emerging threats.