Search results for: equitable resource allocation

Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

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Authors: Dana Aljadaa, Hasim Altan

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Japan’s strategy is based on improving the current resources and productivity by identifying the environmental challenges to progress further in many areas. For example, it will help in understanding the competitive challenges in the industry, emerging innovation, and other progresses. The present study seeks to examine the characteristics of sustainable practices using materials that will last longer and following environmental policies. There has been a major emphasis since 1990s and onwards about recycling and preserving the environment. Furthermore, the present paper analyses and argues how national interest in policy increases resource productivity. It is a universal law, but these actions may be different based on the unique situation of the country. In addition, the present study explains some of the strategies developed by the Environmental Agency of Japan in the last few years. There are a few resources reviewed involving ‘Strategy for an Environmental Nation in the 21st Century’ from 2001, ‘Clean Asia Initiative’ from 2008, and ‘New Growth Strategy’ from 2010. The present paper also highlights the emphasis on increasing efficiency, as it is an important part of sustainability. We finally conclude by providing reasoning on the impact and positivity of reducing production and consumption on the environment, resulting in a productive and progressive Japan for the near and long term future.

Keywords: eco-system, resource productivity, sound material-cycle, sustainable development

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Authors: Dimitrios J. Dimitriou

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Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: airport connectivity, inventory control, optimization, optimum allocation

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Authors: Niringiye Fred

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Banyabunagana has always had access to land resources for grazing animals, sand mining, and farmland across the border in the Democratic Republic of Congo during the pre-colonial and colonial times, usually on an informal arrangement facilitated by kinship ties and rent transactions for these resources. However, in recent periods, the government of the Democratic Republic of the Congo (DRC) has been pursuing a policy of constructing barriers such as walls and fences so that Banyabunagana communities do not access the land on the DRC side of the border. This is happening in the background of increased and intensified demand for land use on the side of the Ugandan community. This paper will attempt to discuss the reasons behind the construction of walls, fences, and other barriers which deny access to land for Banyabunagana communities in Bunagana Parish, Muramba Sub-county- Kisoro district, Uganda. The research will attempt to answer the following main questions, among others, whether there are the factors that explain the construction of walls and fences which could limit or deny access to the informal use of land and other resources and whether policy options to ensure continued access to land and other resources for local communities.

Keywords: border, walls, fences, land resource access

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Authors: Zhang Qingzhong

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Though there exists an increasing number of research studies on the headquarters-subsidiary relationship, and within this context, there is a focus on subsidiaries' contributory role to multinational corporations (MNC), subsidiary autonomy, and the conditions under which autonomy exerts an effect on subsidiary performance still constitute a subject of debate in the literature. The objective of this research is to study the MNC subsidiary autonomy and performance relationship and the effect of subsidiary entrepreneurial orientation and trust on subsidiary autonomy in the China environment, a phenomenon that has not yet been studied. The research addresses the following three questions: (i) Is subsidiary autonomy associated with MNC subsidiary performance in the China environment? (ii) How do subsidiary entrepreneurship and its trust in headquarters affect the level of subsidiary autonomy and its relationship with subsidiary performance? (iii) Does subsidiary autonomy have a mediating effect on subsidiary performance with subsidiary’s entrepreneurship and trust in headquarters? In the present study, we have reviewed literature and conducted semi-structured interviews with multinational corporation (MNC) subsidiary senior executives in China. Building on our insights from the interviews and taking perspectives from four theories, namely the resource-based view (RBV), resource dependency theory, integration-responsiveness framework, and social exchange theory, as well as the extant articles on subsidiary autonomy, entrepreneurial orientation, trust, and subsidiary performance, we have developed a model and have explored the direct and mediating effects of subsidiary autonomy on subsidiary performance within the framework of the MNC. To test the model, we collected and analyzed data based on cross-industry two waves of an online survey from 102 subsidiaries of MNCs in China. We used structural equation modeling to test measurement, direct effect model, and conceptual framework with hypotheses. Our findings confirm that (a) subsidiary autonomy is positively related to subsidiary performance; (b) subsidiary entrepreneurial orientation is positively related to subsidiary autonomy; (c) subsidiary’s trust in headquarters has a positive effect on subsidiary autonomy; (d) subsidiary autonomy mediates the relationship between entrepreneurial orientation and subsidiary performance; (e) subsidiary autonomy mediates the relationship between trust and subsidiary performance. Our study highlights the important role of subsidiary autonomy in leveraging the resource of subsidiary entrepreneurial orientation and its trust relationship with headquarters to achieve high performance. We discuss the theoretical and managerial implications of the findings and propose directions for future research.

Keywords: subsidiary entrepreneurial orientation, trust, subsidiary autonomy, subsidiary performance

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Authors: Eyasu Markos Woldesemayat, Paolo Vincenzo Genovese

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In recent years with an increase in the concentration of Green House Gases (GHG), Climate Change (CC) externalities are mounting, regardless of governments, are scrambling to implement mitigation and adaptation measures. With multiple social, economic and environmental benefits, Green Infrastructure (GI) has evolved as a highly valuable policy tool to promote sustainable development and smart growth by meeting multiple objectives towards quality of life. However, despite the wide range of benefits, it's uptake in African cities such as Addis Ababa is very low due to several constraining factors. This study, through content analysis and key informant interviews, examined barriers for the uptake of GI among spatial planners in Addis Ababa. Added to this, the study has revealed that the spatial planners had insufficient knowledge about GI planning principles such as multi-functionality, integration, and connectivity, and multiscale. The practice of implementing these holistic principles in urban spatial planning is phenomenally nonexistent. The findings also revealed 20 barriers categorized under four themes, i.e., institutional, socio-cultural, resource, and cognitive barriers. Similarly, it was identified that institutional barriers (0.756), socio-cultural barriers (0.730), cognitive barriers (0.700) and resource barriers (0.642), respectively, are the foremost impending factors for the promotion of GI in Addis Ababa. It was realized that resource barriers were the least constraining factor for enshrining the GI uptake in the city. Strategies to hasten the adoption of GI in the city mainly focus on improving political will, harmonization sectorial plans, improve spatial planning and implementation practice, prioritization of GI in all planning activities, enforcement of environmental laws, introducing collaborative GI governance, creating strong and stable institutions and raising awareness on the need to conserve environment and CC externalities through education and outreach mechanisms.

Keywords: Addis Ababa, climate change, green infrastructure, spatial planning, spatial planners

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: A. O. Arowolo, M. U. Agbonlahor, P. A. Okuneye, A. E. Obayelu

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Nigeria is rich with abundant resources with an immense contribution of the forest resource to her economic development and to the livelihood of the rural populace over the years. However, this important resource has continued to shrink because it is not sustainably used, managed or conserved. The loss of forest cover has far reaching consequences on regional, national and global economy as well as the environment. This paper reviewed the Nigeria forest management policies, the challenges and willingness to pay (WTP) for management of the community forests in Ogun State, Nigeria. Data for the empirical investigation were obtained using a cross-section survey of 160 rural households by multistage sampling technique. The WTP was assessed by the Dichotomous Choice Contingent Valuation. One major findings is that, the Nigerian forest reserves is established in order to conserve and manage forest resources but has since been neglected while the management plans are either non-existent or abandoned. Also, the free areas termed the community forests where people have unrestricted access to exploit are fast diminishing in both contents and scale. The mean WTP for sustainable management of community forests in the study area was positive with a value of ₦389.04/month. The study recommends policy measures aimed at participatory forest management plan which will include the rural communities in the management of community forests. This will help ensure sustainable management of forest resources as well as improve the welfare of the rural households.

Keywords: forests, management, WTP, Nigeria

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Authors: Felipe Riveros, Ricardo Alvarez, Claudia Rahmann, Rodrigo Moreno

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Around the world, many countries have committed to a decarbonization of their electricity system. Under this global drive, converter-interfaced generators (CIG) such as wind and photovoltaic generation appear as cornerstones to achieve these energy targets. Despite its benefits, an increasing use of CIG brings several technical challenges in power systems, especially from a stability viewpoint. Among the key differences are limited short circuit current capacity, inertia-less characteristic of CIG, and response times within the electromagnetic timescale. Along with the integration of CIG into the power system, one enabling technology for the energy transition towards low-carbon power systems is battery energy storage systems (BESS). Because of the flexibility that BESS provides in power system operation, its integration allows for mitigating the variability and uncertainty of renewable energies, thus optimizing the use of existing assets and reducing operational costs. Another characteristic of BESS is that they can also support power system stability by injecting reactive power during the fault, providing short circuit currents, and delivering fast frequency response. However, most methodologies for sizing and allocating BESS in power systems are based on economic aspects and do not exploit the benefits that BESSs can offer to system stability. In this context, this paper presents a methodology for determining the optimal allocation of battery energy storage systems (BESS) in weak power systems with high levels of CIG. Unlike traditional economic approaches, this methodology incorporates stability constraints to allocate BESS, aiming to mitigate instability issues arising from weak grid conditions with low short-circuit levels. The proposed methodology offers valuable insights for power system engineers and planners seeking to maintain grid stability while harnessing the benefits of renewable energy integration. The methodology is validated in the reduced Chilean electrical system. The results show that integrating BESS into a power system with high levels of CIG with stability criteria contributes to decarbonizing and strengthening the network in a cost-effective way while sustaining system stability. This paper potentially lays the foundation for understanding the benefits of integrating BESS in electrical power systems and coordinating their placements in future converter-dominated power systems.

Keywords: battery energy storage, power system stability, system strength, weak power system

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Authors: Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

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Multi-reservoir optimization operation has been a critical issue for river basin management. Water, as a scarce resource, is in high demand and the problems associated with the reservoir as its storage facility are enormous. The complexity in balancing the supply and demand of this prime resource has created the need to examine the best way to solve the problem using optimization techniques. The objective of this study is to evaluate the performance of the multi-objective meta-heuristic algorithm for the operation of Gariep Dam for satisfying ecological flow requirements. This study uses an evolutionary algorithm called backtrack search algorithm (BSA) to determine the best way to optimise the dam operations of hydropower production, flood control, and water supply without affecting the environmental flow requirement for the survival of aquatic bodies and sustain life downstream of the dam. To achieve this objective, the operations of the dam that corresponds to different tradeoffs between the objectives are optimized. The results indicate the best model from the algorithm that satisfies all the objectives without any constraint violation. It is expected that hydropower generation will be improved and more water will be available for ecological flow requirements with the use of the algorithm. This algorithm also provides farmers with more irrigation water as well to improve their business.

Keywords: BSA evolutionary algorithm, metaheuristics, optimization, river basin management

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Authors: Hangil Park, Hwayeon Song, Jingyung Sim

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In this study, a business ecosystem of a domestic space industry is comprehensively analyzed to derive the influence factors. The priority level of each element as well as the disparity between the ideal and reality are investigated through a literature review and an expert survey. The three major influence factors determined are: (a) investment scale and approach, (b) propulsion system, and (c) industrialization with overseas expansion. Related issues based on the current status are evaluated, followed by a proposed activation strategy. This research's findings offer a direction for R&D budget allocation and law system maintenance for the activation of the domestic space industry.

Keywords: space industry, activation, strategy, business ecosystem

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Abel Kahuni

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Cooperative game theory (CGT) postulates that groups of players are crucial units of the decision-making and impose cooperative behaviour. Accordingly, cooperative games are regarded as competition between coalitions of players, rather than between individual players. However, the basic supposition in CGT is that the cooperative is formed by all players. One of the emerging questions in CGT is how to develop cooperatives and fairly allocate the payoff. Cooperative Game Theory (CGT) may provide a framework and insights into the ways small holder farmers in rural resettlements may develop competitive advantage through marketing cooperatives. This conceptual paper proposes a non-competition model for small holder farmers of homogenous agri-commodity under CGT conditions. This paper will also provide brief insights into to the theory of cooperative games in-order to generate an understanding of CGT, cooperative marketing gains and its application in small holder farming arrangements. Accordingly, the objective is to provide a basic introduction to this theory in connection with economic competitive theories in the context of small holder farmers. The key value proposition of CGT is the equitable and fair sharing of cooperative gains.

Keywords: game theory, cooperative game theory, cooperatives, competition

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Authors: Zhu Zhizheng, Huang Yong, Li Tong

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In the context of land and space development and resource environmental protection. Due to its special geographical location, mountain-plain transition zones are limited by many factors such as topography, mountain forest protection, etc., and their ecology is also more sensitive, with the characteristics of disaster susceptibility and resource gradient. Taking Dujiangyan City, Chengdu as an example, this paper establishes resilience evaluation indicators on the basis of ecological suitability evaluation through the analysis of current situation data and relevant policies: water conservation evaluation, soil and water conservation evaluation, biodiversity evaluation, soil erosion sensitivity evaluation, etc. Based on GIS spatial analysis, the ecological suitability and resilience evaluation results of Dujiangyan city were obtained by disjunction operation. The ecological resilience level of Dujiangyan city was divided into three categories: high, medium and low, with an area ratio of 50.81%, 16.4% and 32.79%, respectively. This paper can provide ideas for solving the contradiction between man and land in the mountain-plain transition zones, and also provide a certain basis for the construction of regional ecological protection and the delineation of three zones and three lines.

Keywords: urban and rural planning, ecological resilience, dujiangyan city, mountain-plain transition zones

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Authors: Sonia Darshini Singh

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Recently, the Supreme Court and the federal government made affirmative action illegal. Colleges and universities are no longer allowed to consider race in admissions policies. Colleges and universities had the opportunity to increase racial diversity through affirmative action. Instead, a recent educational outlook has emerged where this race-conscious affirmative action is banned, and elitism is prioritized, thus altering the collegiate experience of students of color. While the statute restricts the consideration of race as a facet in admissions, this prohibition should not allow for the gravity of race and structural racism in the lives of marginalized students to diminish, nor should it limit further efforts to establish equitable access and outcomes for students of color. Not much is known about the racialized experiences of students of color who attend predominantly white institutions in the post-affirmative action era. The purpose of this ethnographic study will be to understand the racialized experiences of students who attend predominantly white institutions (PWI) in New York. This also aims to examine the potential data triangulation between what students wrote about to get into college and their actual racialized experience.

Keywords: higher education, predominantly white institution, equity, accessibility, affirmative action

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Authors: M. Dahbi, M. Sellam, A. Benatiallah, A. Harrouz

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The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria The main purpose of this paper is to compared and discuss the wind power potential in three sites located in sahara of Algeria (south west of Algeria) and to perform an investigation on the wind power potential of desert of Algeria. In this comparative, wind speed frequency distributions data obtained from the web site SODA.com are used to calculate the average wind speed and the available wind power. The Weibull density function has been used to estimate the monthly power wind density and to determine the characteristics of monthly parameters of Weibull for these three sites. The annual energy produced by the BWC XL.1 1KW wind machine is obtained and compared. The analysis shows that in the south west of Algeria, at 10 m height, the available wind power was found to vary between 136.59 W/m2 and 231.04 W/m2. The highest potential wind power was found at Adrar, with 21h per day and the mean wind speed is above 6 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 512 KWh and 1643.2 kWh. However, the wind resource appears to be suitable for power production on the sahara and it could provide a viable substitute to diesel oil for irrigation pumps and rural electricity generation.

Keywords: Weibull distribution, parameters of Wiebull, wind energy, wind turbine, operating hours

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Authors: Bill Wang, Paul Childerhouse, Yuanfei Kang

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Purpose: The research is to extend resource orchestration theory (ROT) into supply chain management (SCM) area to investigate the dyadic relationships at both individual and organizational levels in supply chain integration (SCI). Also, we try to explore the interaction mechanism between inter-personal relationships (IPRs) and inter-organizational (IORs) during the whole SCI process. Methodology/approach: The research employed an exploratory multiple case study approach of four New Zealand companies. The data was collected via semi-structured interviews with top, middle, and lower level managers and operators from different departments of both suppliers and customers triangulated with company archival data. Findings: The research highlights the important role of both IPRs and IORs in the whole SCI process. Both IPRs and IORs are valuable, inimitable resources but IORs are formal and exterior while IPRs are informal and subordinated. In the initial stage of SCI process, IPRs are seen as key resources antecedents to IOR building while three IPRs dimensions work differently: personal credibility acts as an icebreaker to strengthen the confidence forming IORs, and personal affection acts as a gatekeeper, whilst personal communication expedites the IORs process. In the maintenance and development stage, IORs and IPRs interact each other continuously: good interaction between IPRs and IORs can facilitate SCI process while the bad interaction between IPRs can damage the SCI process. On the other hand, during the life-cycle of SCI process, IPRs can facilitate the formation, development of IORs while IORs development can cultivate the ties of IPRs. Out of the three dimensions of IPRs, Personal communication plays a more important role to develop IORs than personal credibility and personal affection. Originality/value: This research contributes to ROT in supply chain management literature by highlighting the interaction of IPRs and IORs in SCI. The intangible resources and capabilities of three dimensions of IPRs need to be orchestrated and nurtured to achieve efficient and effective IORs in SCI. Also, IPRs and IORs need to be orchestrated in terms of breadth, depth, and life-cycle of whole SCI process. Our study provides further insight into the rarely explored inter-personal level of SCI. Managerial implications: Our research provides top management with further evidence of the significance roles of IPRs at different levels when working with trading partners. This highlights the need to actively manage and develop these soft IPRs skills as an intangible competitive resource. Further, the research identifies when staff with specific skills and connections should be utilized during the different stages of building and maintaining inter-organizational ties. More importantly, top management needs to orchestrate and balance the resources of IPRs and IORs.

Keywords: case study, inter-organizational relationships, inter-personal relationships, resource orchestration, supply chain integration

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Authors: A. Hidalgo, A. Desportes, E. Bonin, A. Kadaoui, T. Bouaricha

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Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation.

Keywords: Black-Litterman, Markowitz, market data, portfolio manager opinion

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Authors: Aikaterini Kentroti, Theodore H. Kaskalis

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Today, web servers are expected to serve thousands of client requests concurrently within stringent response time limits. In this paper, we evaluate experimentally and compare the performance as well as the resource utilization of popular web servers, which differ in their approach to handle concurrency. More specifically, Central Processing Unit (CPU)- and I/O intensive tests were conducted against the thread-based Apache and Go as well as the event-based Nginx and Node.js under increasing concurrent load. The tests involved concurrent users requesting a term of the Fibonacci sequence (the 10th, 20th, 30th) and the content of a table from the database. The results show that Go achieved the best performance in all benchmark tests. For example, Go reached two times higher throughput than Node.js and five times higher than Apache and Nginx in the 20th Fibonacci term test. In addition, Go had the smallest memory footprint and demonstrated the most efficient resource utilization, in terms of CPU usage. Instead, Node.js had by far the largest memory footprint, consuming up to 90% more memory than Nginx and Apache. Regarding the performance of Apache and Nginx, our findings indicate that Hypertext Preprocessor (PHP) becomes a bottleneck when the servers are requested to respond by performing CPU-intensive tasks under increasing concurrent load.

Keywords: apache, Go, Nginx, node.js, web server benchmarking

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Jordan Fallow

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Service and advocacy organisations that serve refugee populations are often staffed by a large percentage of former refugees themselves, and this carries a number of implications for refugee rights, specifically economic and social rights. This paper makes an argument for the importance of introducing an understanding of intersectionality theory into organizations who provide services to and employ, refugee staff. The benefits of this are threefold; on an individual level it reduces the risks of burn out, vicarious trauma and compassion fatigue while increasing employee satisfaction and development, at an organizational level services become more effective, and at a systems level it helps reduce structural violence, which may itself have been a contributing factor in the movement of refugee staff from their origin countries. In support of this argument, a case study of an Australian settlement services organization is provided. Mixed methods research, utilising both qualitative and quantitative data, measured the perceived efficacy of diversity management tools at the organization and the impact this had on staff performance, retention and wellbeing. The paper also draws on strategic human resource and reward management, diversity management, international development and intersectionality texts.

Keywords: structural violence, employment, human resource management, intersectionality

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Authors: Ruth Yunji Nange

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Tourism has continued to increase as a significant industry, enhancing economic growth and development in Cameroon; due to the tremendous success of this industry, community participation (CP) has enhanced tourism development (TD). While gaining augmented attractiveness, considering how local CP is encouraged in such initiatives has become imperative. It has become essential to examine the importance of CP in the development of policies and planning processes for the equitable distribution of benefits and the effects of TD in the country. This study will exactly explore the cases of CP in the most populated cities in Cameroon (Douala and Yaoundé) and also understand how local CP is incorporated into tourism to enhance development in the tourism industry in particular and Cameroon in general. This paper is based on a qualitative research method, semi-structured interviews, and in-depth, face-to-face interviews carried out with the top administrators of tourism, both in the public and private sectors, such as the minister, provincial and regional delegates of tourism, non-governmental organizations (NGO), leaders of local community associations and tour operators. The forms and surveys were open-ended with a high level of flexibility. The findings of this study will pose implications for the development of CP in tourism initiatives programs in Cameroon and other developing economies.

Keywords: Cameroon, local community, participation and planning, tourism

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Prashansa Singh, Manjot Kaur, Rohit Bajaj

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The proliferation of wireless sensor networks and Internet of Things (IoT) devices in the quickly changing digital landscape has highlighted the urgent need for strong security solutions that can handle these systems’ limited resources. A key solution to this problem is the emergence of ultralightweight security protocols, which provide strong security features while respecting the strict computational, energy, and memory constraints imposed on these kinds of devices. This in-depth analysis explores the field of ultralightweight security protocols, offering a thorough examination of their evolution, salient features, and the particular security issues they resolve. We carefully examine and contrast different protocols, pointing out their advantages and disadvantages as well as the compromises between resource limitations and security resilience. We also study these protocols’ application domains, including the Internet of Things, RFID systems, and wireless sensor networks, to name a few. In addition, the review highlights recent developments and advancements in the field, pointing out new trends and possible avenues for future research. This paper aims to be a useful resource for researchers, practitioners, and developers, guiding the design and implementation of safe, effective, and scalable systems in the Internet of Things era by providing a comprehensive overview of ultralightweight security protocols.

Keywords: wireless sensor network, machine-to-machine, MQTT broker, server, ultralightweight, TCP/IP

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Authors: Ahmadi, Iriansyah, Raihana Yahman

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The giant freshwater prawn (Macrobrachium rosenbergii de Man, 1879) is a valuable species for fisheries and aquaculture, especially in Southeast Asia, including Indonesia due to their high market demand and potential for export. The growing demand for prawns is straining the sustainability of the Banjar Regency fishery. To ensure the long-term sustainability and economic viability of the prawn fishing in this region, it is imperative to implement evidence-based management practices. This requires comprehensive data on the Catch per Unit Effort (CPUE), Maximum Sustainable Yield (MSY) and the current rate of prawn resource exploitation. it analyzed five years of prawn catch data (2019-2023) obtained from South Kalimantan Marine and Fisheries Services. Fishing gears (e.g. hook & line and cast net) were first standardized with Fishing Power Index, and then calculated effort and MSY. The intercept (a) and the slope (b) values of regression curve were used to estimate the catch-maximum sustainable yield (CMSY) and optimal fishing effort (Fopt) levels within the framework of the Surplus Production Model. The estimated rates of resource utilization were then compared to the criteria of The National Commission of Marine Fish Stock Assessment. The findings showed that the CPUE value peaked in 2019 at 33.48 kg/trip, while the lowest value observed in 2022 at 5.12 kg/trip. The CMSY value was estimated to be 17,396 kg/year, corresponding to the Fopt level of 1,636 trips/year. The highest utilization rate was 56.90% recorded in 2020, while the lowest rate was observed in 2021 at 46.16%. The annual utilization rates were classified as “medium”, suggesting that increasing fishing effort by 45% could potentially maximize prawn catches at an optimum level. These findings provide a baseline for sustainable fisheries management in the region.

Keywords: giant prawns, CPUE, fishing power index, sustainable potential, utilization rate

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Authors: Amirul Al-Ashraf Abdullah, Hema Ramachandran, Iszatty Ismail

Abstract:

Oleochemical industry in Malaysia has been diversifying significantly due to the abundant supply of both palm and kernel oils as raw materials as well as the high demand for downstream products such as fatty acids, fatty alcohols and glycerine. However, environmental awareness is growing rapidly in Malaysia because oleochemical industry is one of the palm-oil based industries that possess risk to the environment. Glycerine pitch is one of the scheduled wastes generated from the fatty acid plants in Malaysia and its discharge may cause a serious environmental problem. Therefore, it is imperative to find alternative applications for this waste glycerine. Consequently, the aim of this research is to explore the application of glycerine pitch as direct fermentation substrate in the biosynthesis of poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] copolymer, aiming to contribute toward the sustainable production of biopolymer in the world. Utilization of glycerine pitch (10 g/l) together with 1,4-butanediol (5 g/l) had resulted in the achievement of 40 mol% 4HB monomer with the highest PHA concentration of 2.91 g/l. Synthesis of yellow pigment which exhibited antimicrobial properties occurred simultaneously with the production of P(3HB-co-4HB) through the use of glycerine pitch as renewable carbon resource. Utilization of glycerine pitch in the biosynthesis of P(3HB-co-4HB) will not only contribute to reducing society’s dependence on non-renewable resources but also will promote the development of cost efficiency microbial fermentation towards biosustainability and green technology.

Keywords: biopolymer, glycerine pitch, natural pigment, P(3HB-co-4HB)

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Authors: Eliane Abdo

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Small and medium sized firms “SMEs” play essential role in the countries’ economic development mainly in terms of production, employment and equitable distribution of income. For innovative SMEs, the investment in the human capital and in research and development are crucial to survive in a competitive environment. In this paper we perform a literature review to underline the financing difficulties and constraints which innovative SMEs face while investing in intangible assets: not only when defining amount of the investments but also while choosing its financing methods. Literature review revealed that in order to finance their intangible assets, SMEs rely in first on their internal financing: the availability of internal cash flows can then determine their investment’s decision. Moreover SMEs face difficulties to finance their intangibles by financial debts due to the uncertainty of future cash flow and the absence of physical guarantees; they will therefore go for the issuance of new shares as a second choice, since innovative companies have high opportunity of growth that attract new shareholders.

Keywords: small and medium sized firms, capital structure, intangible investment, financial constraints

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Authors: José Davi Oliveira De Moura, Chou Sin Chan

Abstract:

In this study, the effect of convective momentum transport (CMT) on the life of cyclone systems and their organization is analyzed. A case of strong precipitation, in the southeast of Brazil, was simulated using Eta model with two kinds of convective parameterization: Kain-Fritsch without CMT and Kain-fritsch with CMT. Reanalysis data from CFSR were used to compare Eta model simulations. The Wind, mean sea level pressure, rain and temperature are included in analysis. The rain was evaluated by Equitable Threat Score (ETS) and Bias Index; the simulations were compared among themselves to detect the influence of CMT displacement on the systems. The result shows that CMT process decreases the intensity of meso cyclones (higher pressure values on nuclei) and change the positions and production of rain. The decrease of intensity in meso cyclones should be caused by the dissolution of momentum from lower levels from up levels. The rain production and rain distribution were altered because the displacement of the larger systems scales was changed. In addition, the inclusion of CMT process is very important to improve the simulation of life time of meteorological systems.

Keywords: convection, Kain-Fritsch, momentum, parameterization

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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