Purpose: Over the years, social and environmental reporting has been marred with theories and approaches that lack guidance on how companies can simultaneously uplift lives of social and environmental stakeholders (SEs) while creating measurable economic value. Shared value creation is a new model that promotes simultaneous creation of economic, social and environmental value, in collaboration with social and environmental stakeholders (SEs). This study analyses the level at which Johannesburg Stock Exchange-listed companies (JSE) are collaborating with social and environmental stakeholders in the process of simultaneously creating economic social and environmental value. Methodology: A qualitative interpretive research methodology was used in this study. Random sampling was used for twenty-one interviews from civil society organisations that had participated in protests during the period understudy. Two hundred seventy-eight integrated reports were collected over a period of five years from top 100 JSE-listed companies as soon as they became available. Media reports sample was not predetermined but accumulated as events related to the study occurred. The study adopted grounded theory design for analysing perceptions, experiences of participants and narratives in order to socially construct reality using those interpretations. ATLAS ti software and excel was used to analyse the data. Findings: From the analysis, the study identified weaknesses in collaboration processes. From the interpretations, it emerged that JSE-listed companies intensely involve SE stakeholders in the collection of material concerns but inadequately collaborate with SE stakeholders during implementation process. Originality/Value: The study recommends an improvement in relational collaboration for empowerment of SEs.

This study examines the energy and exergy performance of the Khoy dual fuel combined cycle power plant, focusing on dual pressure heat recovery steam generators (HRSGs). The aim is to identify an optimal design through the development of a thermodynamic model using ASPEN PLUS software. In the simulation, isentropic efficiencies of high-pressure and low-pressure steam turbines, gas turbines, and compressors are assumed to be 0.85, 0.80, 0.85, and 0.85, respectively. Various practical parameters, such as compressor pressure, condenser pressure, high-pressure steam turbine pressure, and outlet and inlet temperatures of superheaters and turbines, are investigated for their effects on energy and exergy efficiencies. The analysis reveals that combustion chamber I and combustion chamber II contribute the highest amounts of exergy destruction, accounting for 21.80% and 21.50% of the total exergy destruction, respectively. These areas are identified as requiring improvement. Based on the findings, an optimal design is presented, resulting in significant enhancements in energy and exergy efficiencies. The energy efficiency experiences a remarkable increase of 8.75%, while the exergy efficiency demonstrates a substantial improvement of 22.04%. This underscores the superiority of the optimized power plant configuration and provides valuable insights for designers, engineers, and power plant operators. In conclusion, this study advances the understanding of the energy and exergy performance of the Khoy dual fuel combined cycle power plant and offers guidance for optimizing its design and operation.

This study introduces a novel approach to decision-making problems, especially in the context of hard disk selection, using the concept of the fuzzy parameterized single-valued neutrosophic soft set (FP-SVNSS). Primarily, the focus is on assigning different levels of importance to each parameter within the set, which enables a more nuanced and flexible evaluation process. This is underpinned by the development of several related concepts and the definition of basic operations such as complement, subset, union, and intersection. In the quest for clarity, the nuances of these operations and the overall framework of the FP-SVNSS method are illustrated via numerous examples. The superiority of the FP-SVNSS method over other decision-making methods is affirmed through a comprehensive comparison. The unique strength of the proposed approach lies in its ability to handle imperfect, ambiguous, and inconsistent data. Consequently, it offers greater accuracy and practicality than existing models. In the latter part of the study, the theory is put to the test by tackling a real-world decision-making problem. The selected case involves the optimal selection of hard disks, a common issue in information technology procurement. The successful application of the FP-SVNSS method to this issue provides a compelling demonstration of its potential value in practical settings. Through the exploration of this innovative decision-making methodology, this research contributes to the broader field of soft computing and decision-making theory. The findings suggest a myriad of future applications of the FP-SVNSS method in dealing with various complex and fuzzy problems in both academic and industrial contexts.

The implementation of Project Management Institute (PMI) methodology has been investigated for its potential benefits in the administration of construction projects and urban planning. Utilizing a mixed-method approach, this study incorporates a broad literature review and detailed case studies to elucidate the influence of the PMI methodology, with a specific focus on project planning and the alignment of activities with project goals. Outcomes demonstrate that this systematic methodology allows for precise articulation of project objectives, scope, timelines, and resources, subsequently promoting rigorous project planning and goal alignment. It has also been revealed that PMI methodology plays a crucial role in risk identification and management, thereby facilitating knowledgeable decision-making and reducing project setbacks. Emphasis is placed on the proactive nature of project management, particularly in complex, multi-stakeholder projects. Furthermore, PMI methodology fosters effective communication and collaboration among team members, thereby enhancing coordination and the attainment of the desired project outcomes. The study indicates that PMI methodology's implementation provides a structured and efficient approach to project execution, subsequently enhancing project quality, efficiency, and stakeholder satisfaction levels. Future research in this field is advocated, along with the endorsement of PMI methodology's adoption within the construction and urban planning industry. As such, this research significantly contributes to the understanding of the PMI methodology's potential to improve project management within the construction and urban planning sectors, demonstrating its capacity to augment quality, efficiency, and satisfaction levels.

In recent years, advances in digital technology have rapidly permeated various business sectors and functions, leading to the digital transformation of numerous traditional paper-based accounting processes. Consequently, e-accounting practices such as e-invoicing, e-archiving, and e-bookkeeping have become increasingly widespread. Although e-accounting applications offer advantages such as cost and time savings, increased efficiency, and reliable data storage, there remain significant obstacles to their adoption. This study investigates the primary limitations hindering the use of e-accounting practices by surveying 100 practicing accountants in Istanbul, Turkey, in 2023. The findings reveal that the primary obstacles perceived by the accountants are an inadequate infrastructure and a lack of qualified personnel. Compared with previous studies on the topic, the sample frame in the present research comprises a wealthier, stronger, and more populous province. However, the results suggest that accountants in different provinces with varying levels of industrialization hold similar views regarding the drawbacks of e-accounting applications. Consequently, nationwide efforts to address infrastructure limitations and skills gaps are crucial for overcoming barriers to e-accounting adoption. By addressing these challenges, Turkish accountants and businesses can fully harness the benefits of digital technology.

The fluctuation in the price of crude oil on the global market has created a lot of attention to the researchers to investigate its price movement. This study tries to address the problem of predicting crude oil prices in a situation of unusual circumstances. In this study, Box Jenkins methodology was used to analyze monthly dynamics of the Brent oil price from January 2002 to February 2022. Data were first differenced to achieve stationarity, and then ACF and residual diagnostics were utilized to choose models that were used for analysis. The performance of various models were evaluated and ARIMA (0, 1, 1) was found to be the best model for forecasting crude oil prices. This study further reveals that despite the corona virus and the Ukraine war having a considerable impact on crude oil prices, such a model is still capable of capturing the underlying volatility in crude oil prices. Oil demand suddenly decreased as a result of the corona outbreak, but then abruptly increased as a result of the conflict in Ukraine. Therefore, there is a need to update the ARIMA model in order to best predict the price of crude oil in a time of exceptional circumstances. Because of the nature of world oil market, predictions for the medium and long term are often therefore, we have limited the scope of our forecasts in this study to a single year in order to achieve the highest level of accuracy.

Hazaribagh is a major source of pollution and a center for the leather industry in Bangladesh. It is home to 1.2 million people and has 185 shoe factories. People who live in Hazaribagh consume surface water and groundwater for drinking and household activities. Implementation of a new law and government pressure has forced several tanneries to shift to areas allocated to industrial parks, but many others have remained. Our research set out to determine the impact of the tanning process on the surface water and groundwater of this area. In this study, surface and groundwater samples (a total of 42) from 6 different points around the tannery complex were analyzed during December 2019 and August 2020 in dry and rainy seasons, respectively. Our main purpose of this study was to find out the quality of the surface and groundwater in the sampling area, as well evaluate the seasonal change of different parameters. During the sampling, we set a route from the tannery source points to the Buriganga River, which is where the tannery effluents end up. The water’s chemical and physicochemical parameters were measured in accordance with the accepted protocol. Our main concern was the presence and concentration of heavy metals which were found to be significantly higher in the first three sampling locations. We also found that heavy metal concentrations dropped dramatically from the river’s upstream source to its final destination, the river Buriganga. Increasing distance from the source site and wastewater percolation to groundwater via soil may have caused this geographical variation in metal concentration. Although, rainwater may have diluted heavy metal concentrations, their levels were still above the permissible level. Heavy metals and other physicochemical parameters, like pH, DO, BOD, TDS, TSS, EC, Cl^``, and Na, were found in all surface and groundwater samples above national (DoE) and international (WHO) standards.

This study proposes a novel annual temperature regulation system for sow houses, integrating heat recovery and photovoltaic-thermal (PV/T) technology to optimize energy utilization efficiency and economic benefits. Mathematical models of key system components are developed and validated using published data, yielding a maximum error of 14.48%. A numerical simulation assesses the system's operating characteristics across different months, revealing the highest total energy consumption and output power in April and August, at 7,298.7 kW and 2.18×104 kW, respectively. Conversely, the lowest energy consumption and output power are observed in November and April, at 2,739.4 kW and 1.10×104 kW, respectively. The results indicate that the system's performance is significantly influenced by external environmental factors. Future research should investigate the system's performance and control strategies in various climatic regions across China, providing theoretical guidance for the application of solar energy and heat recovery in the environmental regulation of sow houses.

The present study scrutinizes the decision-making strategies and enhancement techniques aimed at minimizing progressive collapse in steel moment frame structures. Comparative analyses of both three-story and five-story frames were carried out, focusing on the reinforcement of external frames through the introduction of bracing. Employing ABAQUS, a sophisticated finite element software, simulations of these frames resulted in the exploration of 16 unique steel frame configurations. In an assessment of column loss impact, the middle column of the lowest story in the supporting frame was deliberately removed. Findings reveal that the axial force of the beams adjacent to the removal site in the three-story frame escalates approximately 2.15 times in relation to the values connected with corner beam extraction. Conversely, the increase in axial force of the beams adjacent to the column removal in the five-story frame varied between 5% and 49% of the respective values for beam removal conditions. Furthermore, a reduction in maximum displacement was found to correlate with an increase in the number of stories. Maximum displacements in five-story frames were observed to be roughly 7% to 22% of the corresponding values in three-story frames, with variability depending on the location of the removed column. These results indicate that the effectiveness of bracing-based reinforcement to prevent progressive collapse in steel moment frame structures intensifies with the increase in the number of stories. This performance enhancement against progressive collapse becomes particularly significant for structures comprising a higher number of stories.

The environmental impact of improper waste cooking oil (WCO) disposal can be substantial, resulting in serious implications such as soil contamination, water pollution, energy wastage, and increased greenhouse gas emissions. To mitigate these potential impacts, the conversion of WCO into biodiesel offers an attractive alternative to fossil fuel dependency. This investigation focuses on biodiesel production via transesterification reactions, utilizing WCO collected from local food vendors. Biodiesel yield from Gino, Kings, and Mamador WCO were found to range from 55.5 to 58.1%, 55.1 to 53.9%, and 53.7 to 52.6%, respectively. Furthermore, the specific gravities of the produced biodiesel from Gino, Kings, and Mamador WCO ranged between 0.725-0.75, 0.73-0.84, and 0.71-0.80, respectively. Acid values varied from 0.51-0.52 KOH/g for Gino WCO, 0.50-0.57 KOH/g for Kings WCO, and 0.50-0.57 KOH/g for Mamador WCO. Cetane numbers were observed to range from 45.82-46.25 min for Gino WCO, 46.2-46.45 min for Kings WCO, and 46.0-46.25 min for Mamador WCO. Finally, the flashpoints ranged between 135-138℃ for Gino WCO, 137-140℃ for Kings WCO, and 137-138℃ for Mamador WCO, while cloud points hovered between 4.82-5.02℃. Significantly, all physicochemical properties of the resulting biodiesel were found to be within ASTM recommended parameters, highlighting the potential of WCO as a valuable resource for sustainable biodiesel production.

The aim of this paper is to assess the effect of foreign direct investment on economic growth in Tajikistan. Using annual time series data for 2005 to 2021, the study reveals a relationship between foreign direct investment and per capita GDP growth in Tajikistan. Based on the analysis of the Vector Error Correction Model (VECM), it has been found that these variables have a long-term relationship. The residuals of the regressions showed no autocorrelation in the post-estimation diagnostic tests performed to determine the validity of the VECM model. Furthermore, our findings suggest that improving the institutional quality of the country complements the improvement of the investment climate and results in significant increases in foreign direct investment inflows.

Purpose: The implementation of the lockdown on 28th March 2020 due to the COVID-19 pandemic disrupted business and economic activities completely, which has serious consequences for SMME survival in South Africa and the world at large. Subsequently, there was a contingent need to provide funding to SMMEs to ensure their survival. This study, therefore, explored the meaning of SMME in the South African context and their experiences during the COVID-19 pandemic. The study further investigated the palliative funds given to SMMEs during COVID-19 by the South African government, the challenges encountered during its implementation process, and the measures to improve the funding implementation.

Methodology: The study adopted a qualitative research approach with an exploratory research design, and this enhanced in-depth findings through the adoption of interviews as the only source of primary data collection. Data collected from the participants were analyzed using a thematic analytical technique with the help of Atlas-ti software (Version 22).

Findings: Findings obtained from the study revealed that SMMEs are separate and distinct business entities, including co-operatives and non-governmental organizations (NGOs), managed by one or more owners, including their branches and subsidiaries. Another finding revealed that during the COVID-19 period, SMMEs experienced supply chain disruptions, inventory shortages, cash flow issues, and low income due to the inability to engage in active business. In the empirical study, participants attested that the scoring system, lack of business and managerial experience, communication barriers, and business registration requirements are some of the challenges encountered in funding implementation by the government departments. Furthermore, the participants highlighted that funding based on merit, consideration of the scoring system, and the application of communication dynamics to reach SMMEs should be applied to improve SMME funding implementation.

Originality/Value: This study is meant to inform the government on how to handle SMME funding and measures to assist them to enhance employment and to improve economic development.

This study presents an advanced generalization of uncertain linguistic numbers (ULNs) and interval-valued intuitionistic uncertain linguistic numbers (IVIULNs) through the development of interval-valued picture fuzzy numbers (IVPFNs). Firstly, the IVPFUL weighted average and IVPFUL weighted geometric operators, denoted as IVPFULWA and IVPFULWG, have been introduced. Furthermore, the IVPFUL Dombi weighted average and geometric operators, represented by IVPFULDWA and IVPFULDWG, are also proposed in the same context. These operators are utilized to establish a multi-attribute decision-making (MADM) approach with IVPFUL data. Finally, the proposed methodology is applied to a mutual fund selection problem through a demonstrative example.

Unmanned Aerial Vehicles (UAVs), in the form of ornithopters, which emulate avian flight through wing flapping, have been the focus of this investigation. The remarkable maneuverability of birds and insects, often lacking in conventional aircraft, is harnessed to advance the control and stability of flapping wing flight. The need for such exploration is driven by the potential benefits to both scientific inquiry and societal applications. This investigation tackles the task of tailoring the ornithopter's design and component choice to cater to performance expectations derived from the flight attributes of birds, such as superior maneuverability, agility, low-speed flight capabilities, and high propulsive efficiency. The primary goal is to ensure a sustained airborne state through the generation of lift equivalent to the ornithopter's weight. Commonly available materials have been employed in the construction of the ornithopter. SolidWorks flow simulator was utilized to simulate aerodynamics. A 1000mm length of the wing was subjected to a 3m/s air stream at a 5-degree angle of attack for the simulation. The simulated result, which represents a 2kg ornithopter, exhibited a lift force of 0.8N and a drag force of 0.2N. Further simulations were conducted at varying attack angles (from 0 to 35 degrees) to gauge the range of lift and drag coefficients. The investigation concludes that the constructed ornithopter should generate an upward thrust of 2.7N at a speed of 5m/s, even without wing flapping, ensuring controlled and stable flight.

Purpose: This article analysed the effect of macroeconomic variables on 21 DSE-listed firms from 2006 to 2021 due to past inconclusive results from other research across the globe. Methodology: Mixed-sequential explanatory research design was used. Secondary panel data were collected from DSE while qualitative data was collected via semi structured interviews. Random effect model and thematic analysis were utilized for data analysis. Findings: The study found that GDP, inflation, and money supply had significant positive coefficients, while interest rates and exchange rates had significant negative coefficients, indicating that macroeconomic conditions have a substantial effect on firm performance. Practical implications: The findings suggest that firms should proactively manage macroeconomic conditions to remain competitive and sustainable. Originality/Value: The study's uniqueness lies in its use of qualitative data to support quantitative findings and its examination of the link between macroeconomic conditions and listed firm performance in Tanzania, where little similar research has been conducted.