The University of Professional Studies, Accra (UPSA) formerly known as Institute of Professional Studies (IPS), is a public university in Ghana. The main campus is located in Accra. UPSA is the first university in Ghana to provide both academic and business professional education. The University of Professional Studies Act, 2012 (Act 850) changed the name of the Institute of Professional Studies to University of Professional Studies, Accra. UPSA is nationally and internationally accredited by the National Accreditation Board (Ghana) and the Accreditation Council for Business Schools and Programs (ACBSP) respectively.It introduced the dual qualification scheme for its students ahead of the 2019/20 academic year. With this new system, the students will be required to complete a chartered program such as the ACCA, ICAG, CIM, CIMA, ICSA and others, by the end of their degree study to better enhance their chances of employment in the job market.
This study examines the impact of CEO trust and organizational commitment on global partnerships and sustainable industrial development (SDG 9) among small and medium-sized enterprises (SMEs) in emerging economies, specifically Ghana. It explores the mechanisms through which internal organizational dynamics facilitate external collaboration aligned with Sustainable Development Goal 17 (Partnerships for the Goals). A quantitative research approach was adopted, employing stratified random sampling to survey SME CEOs across various industrial sectors in Ghana. Data collection involved a self-administered questionnaire utilizing validated scales. Structural equation modeling (SEM) tested the hypothesized relationships among CEO trust, organizational commitment, global partnerships, and sustainable industrial development. The results confirm that CEO trust significantly predicts global partnerships and organizational commitment. Organizational commitment positively influences global partnerships, driving sustainable industrial development sustainability. Organizational commitment mediates the CEO trust-global partnerships relationship, while global partnerships mediate the CEO trust-sustainable industrial development link. This study enriches social capital theory, highlighting CEO trust and organizational commitment’s role in facilitating effective global partnerships. It advances sustainable development literature, providing empirical evidence on SMEs in emerging economies harnessing internal leadership and collaborative capacity to achieve SDG 9. The findings offer insights for SME leaders, policymakers, and development agencies promoting industrial growth via strategic international partnerships, contributing to sustainable development goals.
In the quest to identify factors stimulating employee morale, this study assesses the relationship between leadership practices and employee morale via job satisfaction. We employ a quantitative approach, surveying 400 Ghanaian hospitality workers. We analyze the cross-sectional data using SPSS via descriptive statistics, exploratory factor analysis (EFA), and mediation modeling (macro-PROCESS). Transformational, transactional, and democratic leadership relate positively to employee morale, whereas autocratic leadership relates negatively. Job satisfaction significantly mediates the relationship between transformational, transactional, and democratic leadership and employee morale, but not in the case of autocratic leadership. Managers in Ghana’s hospitality industry should prioritize democratic and transactional leadership to boost morale via job satisfaction. Having confirmed the efficacy of the four common leadership practices as antecedents of organizational outcomes without violating the principle of multicollinearity, we provide empirical support for the expansion of the full-range leadership theory (FRLT) to include democratic and autocratic styles. Consequently, this study provides empirical evidence for practitioners and contributes to the limited literature on leadership and employee morale in developing countries.
This paper presents a three-dimensional (3D) stochastic geometry framework to analyze intelligent reflecting surface (IRS) – assisted hybrid beamforming in massive MIMO downlink systems under imperfect channel state information (CSI). Leveraging stochastic geometry, user locations are modeled by a three-dimensional homogeneous Poisson point process (3D-HPPP), enabling tractable spatial averaging of distance distributions, angle spreads, and interference statistics. Both the direct BS–UE link and the cascaded BS–IRS–UE link incorporate geometry-dependent estimation errors that are correlated with spatial positions and LoS probabilities. We derive robust lower bounds on the per-user Signal-to-Interference-plus-Noise Ratio (SINR) and the corresponding sum spectral efficiency (SE) by treating channel estimation errors as additional interference, yielding tractable expressions that quantify the degradation across SNR, CSI error variance, and IRS size. A holistic evaluation covering SE, energy efficiency (EE), and bit error rate (BER) reveals four key insights: (i) finite IRS phase resolution induces BER floors at high SNR, with diminishing returns beyond 3–4 bits; (ii) an IRS-assisted hybrid architecture approaches the performance of a fully digital system while using far fewer RF chains; (iii) CSI errors dominate performance at high SNR, highlighting the need for accurate channel acquisition; and (iv) EE is non-monotonic in the number of IRS elements due to IRS controller/circuit power, yielding an EE-optimal IRS size. Notably, under moderate CSI errors (e.g., σ _e^2=0.05 at 20 dB), the system retains over 80 σ _e^2 = 0.01 , dictating a specific order of priority for hardware upgrades.
This study sought to ascertain whether Hofstede’s cultural dimensions are good predictors of cyberbullying behaviour among Ghanaian tertiary students, given that cultural values can shape individuals’ perceptions and actions, including what is considered acceptable during conflicts in digital spaces. This study used a quantitative, cross-sectional survey design to collect data from 301 tertiary students in Ghana. The data was analysed using structural equation modelling. The model explained 22.9
Sentiment analysis (also known as opinion mining) is a natural language processing (NLP) technique for determining data’s positive, negative, or neutral nature. The rise of social media platforms such as X (formally Twitter) and Facebook have become great arenas for discourse on racism and mediums of racism ideologies. This study utilized a hybrid sentiment analysis to detect racist tweets using lexicon-based sentiment analysis and a Support Vector Machine. The models’ success in accurately classifying sentiments related to racism highlights its potential for broader applications in the analysis of other social issues. Furthermore, this study contributes to the ongoing discourse on combating racism in the digital age. By shedding light on the sentiments expressed online, it provides valuable insights that can inform policy decisions, advocacy efforts, and public awareness campaigns. The findings underscore the importance of addressing racism not just in the physical world but also in the digital sphere, where harmful ideologies can spread rapidly and widely.
