This article aims to provide an in-depth analysis of the global scientific output on the relationship between Islamic banking and economic growth. Adopting a bibliometric approach, the study covers the period from 2007 to 2024 using data retrieved from the Scopus database, a leading source for tracking academic production. The analysis was conducted with VoSviewer software, which enabled the identification of key research themes, influential authors, countries, institutions, and journals shaping the literature in this area.
The results reveal that Malaysia stands out as the most productive country, followed by other Asian and Middle Eastern economies, reflecting the regional importance of Islamic finance. The findings further highlight an evolution in research focus: while early studies were mainly concerned with the resilience of Islamic banking during the global financial crisis, more recent contributions emphasize emerging issues such as financial inclusion, governance, and sustainability.
Overall, the study demonstrates the diversification of research directions and the growing academic interest in Islamic finance, underscoring its potential contribution to inclusive and sustainable economic development.
Business mathematics. Commercial arithmetic. Including tables, etc., Business records management
William De Michele, Abel Armas Cervantes, Lea Frermann
Business processes are fundamental to organizational operations, yet their optimization remains challenging due to the timeconsuming nature of manual process analysis. Our paper harnesses Large Language Models (LLMs) to automate value-added analysis, a qualitative process analysis technique that aims to identify steps in the process that do not deliver value. To date, this technique is predominantly manual, time-consuming, and subjective. Our method offers a more principled approach which operates in two phases: first, decomposing high-level activities into detailed steps to enable granular analysis, and second, performing a value-added analysis to classify each step according to Lean principles. This approach enables systematic identification of waste while maintaining the semantic understanding necessary for qualitative analysis. We develop our approach using 50 business process models, for which we collect and publish manual ground-truth labels. Our evaluation, comparing zero-shot baselines with more structured prompts reveals (a) a consistent benefit of structured prompting and (b) promising performance for both tasks. We discuss the potential for LLMs to augment human expertise in qualitative process analysis while reducing the time and subjectivity inherent in manual approaches.
This paper investigates how individual entrepreneurs can turn creative ideas into successful solo businesses in an era increasingly shaped by Artificial Intelligence (AI) agents. It highlights the key steps that connect personal vision, structured experimentation, and lasting value creation, and shows how AI agents can act as digital co-founders throughout this journey. Building on research in entrepreneurship, creativity, and innovation, we present a framework with three key stages: (1) Imagination shaping, where vague goals become clear value propositions, supported by AI agents that help with market scanning, idea refinement, and rapid concept generation; (2) Reality testing, where these ideas are tested through low-cost experiments, structured feedback loops, and efficient execution, with AI agents automating tasks such as prototyping, content creation, customer interaction, and data analysis; and (3) Reality scaling, where successful ideas are transformed into repeatable processes, scalable market strategies, and long-term business models, increasingly operated and optimized by autonomous or semi-autonomous AI workflows. We focus on the specific context of solopreneurship, characterized by limited human resources, complete accountability for decision-making, and a strong association between the founder's identity and the business. The framework clearly identifies key enabling factors such as mental adaptability, effective planning, and successful human-AI collaboration within digital ecosystems. It also thoughtfully addresses ongoing challenges, like uncertainty and cognitive overload, which are heightened by our constant connectivity.
Illicit Massage Businesses (IMBs) are a covert and persistent form of organized exploitation that operate under the facade of legitimate wellness services while facilitating human trafficking, sexual exploitation, and coerced labor. Detecting IMBs is difficult due to encoded digital advertisements, frequent changes in personnel and locations, and the reuse of shared infrastructure such as phone numbers and addresses. Traditional approaches, including community tips and regulatory inspections, are largely reactive and ineffective at revealing the broader operational networks traffickers rely on. To address these challenges, we introduce IMBWatch, a spatio-temporal graph neural network (ST-GNN) framework for large-scale IMB detection. IMBWatch constructs dynamic graphs from open-source intelligence, including scraped online advertisements, business license records, and crowdsourced reviews. Nodes represent heterogeneous entities such as businesses, aliases, phone numbers, and locations, while edges capture spatio-temporal and relational patterns, including co-location, repeated phone usage, and synchronized advertising. The framework combines graph convolutional operations with temporal attention mechanisms to model the evolution of IMB networks over time and space, capturing patterns such as intercity worker movement, burner phone rotation, and coordinated advertising surges. Experiments on real-world datasets from multiple U.S. cities show that IMBWatch outperforms baseline models, achieving higher accuracy and F1 scores. Beyond performance gains, IMBWatch offers improved interpretability, providing actionable insights to support proactive and targeted interventions. The framework is scalable, adaptable to other illicit domains, and released with anonymized data and open-source code to support reproducible research.
M. Luisa Martínez, Rodolfo Silva, Octavio Pérez-Maqueo
et al.
The real estate business on sandy coasts and coastal dunes has increased dramatically over the last decades because of the growing demands for leisure activities which, consequently, have yielded important economic gains. Such ravaging exploitation results in the replacement of sandy ecosystems with tourism-oriented settlements, infrastructure, and facilities. As the sandy beaches and coastal dunes become deteriorated or eliminated, their protective role is lost, and the hydrometeorological risks to which the increasing human coastal populations are exposed grow, especially in a climate change scenario with increasing storminess. Furthermore, when possible, the expansion of the tourism industry continues searching for new, unspoiled locations, and the cycle begins again. This situation leads to the dilemma of coastal management: should we continue with the over-exploitation of sandy coasts for growing economic benefits? Or should we preserve the coasts for protection against the impact of increasing storms and sea level rise and to benefit biodiversity? Although scientific evidence demonstrates the relevance of protecting the coasts, coastal development plans continue to ignore these findings. What are the key drivers for these trends? We first looked for scientific evidence of the appraisal of the esthetic beauty of the beach and coastal dunes, as highly important drivers of urbanization and coastal environmental change. We then looked for evidence that demonstrated how coastal dunes offer storm protection Finally, we examined if the conservation of beaches and coastal dunes can be compatible with non-intrusive tourism. In summary, through the literature review and our own data, we show how different alternatives may help achieve a more sustainable coastal tourism by combining economic necessities with environmental concerns.
Harbors and coast protective works. Coastal engineering. Lighthouses, Oceanography
Quentin Romero Lauro, Jeffrey P. Bigham, Yasmine Kotturi
Small business owners stand to benefit from generative AI technologies due to limited resources, yet they must navigate increasing legal and ethical risks. In this paper, we interview 11 entrepreneurs and support personnel to investigate existing practices of how entrepreneurs integrate generative AI technologies into their business workflows. Specifically, we build on scholarship in HCI which emphasizes the role of small, offline networks in supporting entrepreneurs' technology maintenance. We detail how entrepreneurs resourcefully leveraged their local networks to discover new use cases of generative AI (e.g., by sharing accounts), assuage heightened techno-anxieties (e.g., by recruiting trusted confidants), overcome barriers to sustained use (e.g., by receiving wrap-around support), and establish boundaries of use. Further, we suggest how generative AI platforms may be redesigned to better support entrepreneurs, such as by taking into account the benefits and tensions of use in a social context.
The construction and development of the Blue Economic Zone on the Shandong Peninsula in China was elevated to a national strategy in 2011, and it has achieved year-on-year economic growth, driving the economic development of Shandong Province. However, it has also generated problems, such as a fragile ecological environment, unbalanced regional development, and prominent human–land conflicts. Therefore, on the basis of the idea of green sustainable development, this paper measures the ecological welfare performance of seven prefecture-level cities in the Blue Economic Zone of Shandong Peninsula from 2011 to 2020 using an entropy-weighted model together with the TOPSIS method. It then analyzes their spatial distribution characteristics using the natural breaks method. Our findings show that the overall ecological welfare performance level in the Shandong Peninsula BEZ shows a stable upward trend, and that the ecological welfare performance of each city is similar to that of the divided region. The ecological welfare performance levels of Weifang, Rizhao, and Binzhou are relatively low. Dongying, Weihai, Qingdao, and Yantai form a cluster of cities with high ecological welfare performance. Therefore, for the advancement of the Shandong Peninsula BEZ, the government should the government should reasonably deploy the industrial structure; actively implement industrial transformation; strengthen the synergistic development among cities to achieve complementary advantages, coordinating the growth of rural and urban areas; and improve the social security system to achieve high-quality sustainable development in the Shandong Peninsula BEZ.
The article highlights the significance of the resource and innovation potential of industrial housebuilding enterprises
in the context of the rapidly changing global economic environment. The author emphasizes the need to develop a mechanism for a comprehensive assessment of this potential in order to provide a comprehensive understanding of the strengths and weaknesses of the enterprise and to identify areas for improvement. The proposed mechanism for assessing resource and innovation potential takes into account both internal and external factors affecting the enterprise. The authors suggest that this approach can lead to a more accurate and reliable evaluation of the enterprise's potential, as it considers both the resources available to the enterprise and the external factors that may impact its performance.
The article also points out the importance of risk management in the enterprise capacity assessment process. The proposed mechanism takes into account risks and uncertainties associated with the activities and development of an enterprise, allowing decision-makers to identify potential risks and develop appropriate strategies to manage them. The study concludes that the proposed mechanism can be used as a tool for decision-making related to the development of industrial housebuilding enterprises. The authors suggest that the results of the study can be of interest to specialists in the field of innovation management, risk management, and industrial housebuilding, as well as to business owners and government agencies involved in the development of this sector.
This article illustrates the measures adopted by the Lombardy Region to plan peri-urban areas at the regional level. These territories typically have urban and rural characteristics and extend beyond municipal administrative boundaries. Their characteristics and extension prevent their precise delimitation and make it difficult to elaborate plans that can effectively regulate their development. These difficulties appear insurmountable for some municipalities that ignore these territories in their planning instruments or regulate only that part of the peri-urban territory within their administrative limits. Decisions at the regional level are relevant to overcome these difficulties. Planning at the municipal level transposes regional prescriptions. In contrast, jurisdiction at the regional level is supra-municipal and, therefore, potentially enables the reduction of the existing gap between governance and peri-urban patterns at the local level. The relevance of regional intervention in the regulation and spatial planning of peri-urban areas has been particularly tested in Lombardy. As demonstrated by a documental analysis concerning spatial planning laws and plans, this region is one of the few Italian regions to have developed specific legislative and planning documents to promote the balance between urban and rural areas in peri-urban areas. Lombardy has introduced specific measures for agri-environmental balance and urban regeneration in peri-urban areas in these documents. However, it must still provide detailed prescriptions for their delimitation or governance. Nothing is mentioned as regards the macro-region that starts in northern Lombardy and extends to Emilia- Romagna. However, interregional cooperation is promoted through the organization of working tables, the signing of specific agreements, and the development of coordinated cartography.
Questo articolo illustra le misure adottate da Regione Lombardia per governare le aree periurbane a livello regionale. Questi territori hanno caratteristiche tipica- mente urbane e rurali e si estendono oltre i confini amministrativi comunali. La varietà di tali caratteristiche e l’estensione sovra-comunale ne impediscono una precisa delimitazione e rendono difficile l’elaborazione di piani che ne regolino efficacemente lo sviluppo. Queste difficoltà appaiono insormontabili per alcuni comuni che ignorano questi territori nei loro strumenti di pianificazione o regolano solo la parte del territorio periurbano che rientra nei loro limiti amministrativi. Le decisioni a livello regionale sono importanti per superare queste difficoltà. La giurisdizione a livello regionale è sovracomunale e, pertanto, consente potenzialmente di ridurre il divario esistente tra governance e modelli periurbani a livello locale. La rilevanza dell’intervento regionale nella regolamentazione e nella pianificazione territoriale delle aree periurbane è stata sperimentata in Lombardia. Questa regione è una delle poche regioni italiane ad aver sviluppato documenti legislativi e di pianificazione specifici per promuovere l’equilibrio tra aree urbane e rurali nelle aree periurbane. Come dimostrato da un’analisi documentale delle leggi e dei piani di pianificazione territoriale, la regione ha introdotto in questi documenti mi- sure specifiche per l’equilibrio agro-ambientale e la rigenerazione urbana nelle aree periurbane. Tuttavia, deve ancora fornire prescrizioni dettagliate per la loro delimitazione o governance. Nulla viene detto per quanto riguarda la macro-regione che parte dalla Lombardia settentrionale e si estende all’Emilia-Romagna. Tuttavia, la cooperazione interregionale viene promossa attraverso l’organizzazione di tavoli di lavoro, la firma di accordi specifici e lo sviluppo di una cartografia coordinata.
The real estate market is affected by great uncertainty due to the nexus of various factors: a) the specificity of the assets traded, which are illiquid, unique and very hetherogeneous from each other; b) the ‘structural disequilibrium’ of the market caused by the differences emerging in elasticity of supply with respect to demand; c) the non-competitiveness of the market, which often turns into a bilateral monopoly; d) the great variability of market prices. Since the subprime mortgage crisis that broke out at the end of 2006 in the United States, it has clearly emerged that, in a sector that represents about a third of world wealth, it is necessary, on the one hand, to implement proper and increasingly sophisticated valuation tools, to support the design of effective risk management strategies and, on the other hand, to improve the reliability of real estate data, in order to allow for a more robust verification of the hypotheses on the trend of the cash flows generated by the investment and a more accurate valuation of the investment risk and, consequently, of the project expected rate of return. The main objective of this work is to investigate the accuracy and robustness of the estimates of real estate investors of the expected returns on an urban development project in a medium-sized city representative of the North East of Italy. Using a simulation-based approach, the gap between the observed internal rate of return, estimated ex post on the basis of the actual trend of the parameters that influence investment returns, and the expected internal rate of return, calculated ex ante on the basis of the information available at the time of the investment decision. Firstly, we constructed the time series from 1995 to 2015 of the expected and observed internal rates of return of investments in the residential sector. We obtained the time series of the cash flows generated by the investment under investigation by implementing a simulation-based approach. Starting from the comparison between observed internal rate of return and expected internal rates of return, we identified ex post the risk implicitly assumed by the investor at the time of the decision to undertake the investment. Secondly, the effectiveness of the Capital Asset Pricing Model as a method for estimating the return on a property investment was verified, by comparing the project’s observed (ex post) internal rate of return with its ex ante rate of return, estimated through the Capital Asset Pricing Model. To carry out the above analyses, we constructed the time series of observed and expected internal rate of returns from 1995 to 2015 of investments in the residential sector. The time series of the internal rate of returns of real estate investments were obtained by implementing a simulation-based approach to determine the cash flows of real estate investments representative of the context under investigation and by adopting as model inputs the parameters usually adopted in ex-ante and ex-post real estate valuations. Starting from the comparison between observed and expected internal rate of returns, we identified ex-post the risk implicitly assumed by the developer at the time of the decision to undertake the investment. Finally, by investigating the determinants of the divergence between the investment’s observed and expected internal rate of return and cyclical variables, we identified the factors (i.e., the macroeconomic fundaments) which, in the period under investigation, affected investment risk and, consequently, investment return. Finally, by investigating the relationships that account for the difference between the observed and expected internal rate of return and the economic factors that can determine the current stage in economic cycles, we identified the determinants of invetment risk and returns.
Il mercato immobiliare è affetto da grande incertezza dovuta a una concatenazione di diversi fattori: a) la specificità dei beni scambiati che sono illiquidi, unici e molto eterogenei tra loro; b) il “disequilibrio strutturale” del mercato causato dalla diversa elasticità del- l’offerta rispetto alla domanda; c) la non concorrenzialità del mercato che, assume spesso le caratteristiche del monopolio bilaterale; d) la grande variabilità dei prezzi di mercato. A partire dalla crisi dei mutui sub- prime scoppiata alla fine del 2006 negli Stati Uniti, è emerso chiaramente come, in un settore che rappresenta circa un terzo della ricchezza mondiale, sia necessario, da un lato, operare con strumenti valutativi adeguati e sempre più sofisticati, in grado di suppor- tare l’individuazione di strategie efficaci di gestione dei rischi e, dall’altro, migliorare l’affidabilità dei dati immobiliari, in modo da consentire una verifica più ro- busta delle ipotesi sull’andamento dei flussi di cassa generati e una stima più accurata del rischio e, conseguentemente, del tasso di rendimento atteso. Obiettivo principale del presente lavoro è di investigare l’accuratezza delle previsioni effettuate da un ipotetico operatore immobiliare sul rendimento di un investi- mento a sviluppo in una città di medie dimensioni rap- presentativa della provincia dell’Italia settentrionale. Attraverso un approccio basato sulla simulazione, è stato calcolato lo scarto fra il tasso interno di rendimento effettivo, stimato ex post in base all’andamento effettivo dei parametri influenti sul rendimento stesso, e il tasso interno di rendimento atteso, calcolato ex ante sulla base delle informazioni disponibili al mo- mento della decisione d’investimento. In primo luogo, è stata costruita la serie storica dal 1995 al 2015 dei tassi interni di rendimento attesi ed effettivi dell’investi- mento immobiliare residenziale a sviluppo. Le serie storiche sono state ottenute mediante la simulazione dei flussi di cassa di investimenti immobiliari rappresentativi della realtà indagata. A partire dal confronto fra tassi interni di rendimento effettivi e tassi interni di rendimento attesi è stato individuato, ex post, il rischio assunto implicitamente dall’investitore al momento della decisione di intraprendere l’investimento stesso. In secondo luogo, è stata verificata la bontà del Capital Asset Pricing Model come metodo di stima del rendi- mento di un investimento immobiliare a sviluppo, confrontando il tasso interno di rendimento effettivo e il tasso di rendimento ex ante stimato attraverso il Capi- tal Asset Pricing Model stesso. Infine, indagando sulle relazioni che intercorrono fra lo scarto fra tasso di rendimento interno effettivo e atteso e le variabili congiunturali, sono stati individuati i fattori che, nel periodo considerato, hanno maggiormente influito sul rischio al quale si è esposto l’investitore al momento di investire.
Pedro das Neves Rodrigues, Alberto Rodrigues da Silva
This study examines the use of controlled natural languages (CNLs) to specify business intelligence (BI) application requirements. Two varieties of CNLs, CNL-BI and ITLingo ASL (ASL), were employed. A hypothetical BI application, MEDBuddy-BI, was developed for the National Health Service (NHS) to demonstrate how the languages can be used. MEDBuddy-BI leverages patient data, including interactions and appointments, to improve healthcare services. The research outlines the application of CNL-BI and ASL in BI. It details how these languages effectively describe complex data, user interfaces, and various BI application functions. Using the MEDBuddy-BI running example.
This review examines the scientific articles of the last decade, approaching the subject through the methodology of the scoping literature review. Starting with the Boolean search global citizens AND education AND (international business OR international business school) in the ScienceDirect, Emerald, and Scopus databases, the review resulted in only scientific journal articles, strictly targeted at tertiary education ONLY of international business schools and ONLY in those articles that study global citizenship. For reasons of up-to-date knowledge, the present literature was content with the final decade. A total of 13 articles are recorded as a result of the aforementioned Boolean search from a total of 216 articles identified in the first phase of the search. The results will help the researchers to acquire the required knowledge base for their research, the academics to incorporate new methods in their teaching and the approach of their students, and the policymakers to adapt the schools curricula according to the data from the articles present in the literature review.
The capability of video super-resolution (VSR) to synthesize high-resolution (HR) video from ideal datasets has been demonstrated in many works. However, applying the VSR model to real-world video with unknown and complex degradation remains a challenging task. First, existing degradation metrics in most VSR methods are not able to effectively simulate real-world noise and blur. On the contrary, simple combinations of classical degradation are used for real-world noise modeling, which led to the VSR model often being violated by out-of-distribution noise. Second, many SR models focus on noise simulation and transfer. Nevertheless, the sampled noise is monotonous and limited. To address the aforementioned problems, we propose a Negatives augmentation strategy for generalized noise modeling in Video Super-Resolution (NegVSR) task. Specifically, we first propose sequential noise generation toward real-world data to extract practical noise sequences. Then, the degeneration domain is widely expanded by negative augmentation to build up various yet challenging real-world noise sets. We further propose the augmented negative guidance loss to learn robust features among augmented negatives effectively. Extensive experiments on real-world datasets (e.g., VideoLQ and FLIR) show that our method outperforms state-of-the-art methods with clear margins, especially in visual quality. Project page is available at: https://negvsr.github.io/.
We investigate liquidity spillovers among industry sectors in the S&P 500 index to explain the interconnection dynamics in the US stock market. To do so, we define a sectoral liquidity measure based on the Amihud liquidity measure. Employing the spillover model, we further examine US sectors' liquidity spillovers during the global financial crisis (GFC) and the COVID-19 pandemic. Based on the relationship between liquidity in financial markets and business cycles, our findings show that (i) liquidity connections became stronger during both crises, (ii) in the GFC period, the material sector was the primary transmitter of total liquidity spillovers, whereas in the COVID-19 pandemic period, the consumer discretionary sector was the main conveyor of total liquidity spillovers and the real estate sector was the dominant recipient of total liquidity spillovers, and (iii) net liquidity spillovers between all sectors fluctuated notably during the GFC, while the industrial, consumer staples, and healthcare sectors had the largest net liquidity spillovers during the COVID-19 crisis. These findings have important implications for portfolio managers and policymakers.
Wojewnik-Filipkowska Anna, Koszarek-Cyra Aleksandra
The airport may be an opportunity for the development of airport-proximate areas, as well as a source of conflicts and nuisances for stakeholders. From the perspective of spatial order and sustainable development, it is necessary to create a coherent vision of the development and operationalize it via spatial management. This article aims to analyze spatial management in areas proximate to Gdansk Airport in the context of spatial chaos. The analyses are based on 232 local spatial development plans for the period 1996-2020, for 11 selected areas in the vicinity of the Gdansk Lech Walesa Airport, documents obtained from the local government, and open-source data. The research concentrates on the analysis of the functions of areas, spatial chaos, and the threat of potential conflicts. The results demonstrate the spatial chaos in proximate areas of Gdansk Airport. This implies that the decisions made by the authorities responsible for spatial management do not respect spatial order and sustainable development and contribute to spatial chaos.
Solving a Riccati equation, induced by the study of the transient behaviour of the MGInf queue system, a collection of service times distributions is determined. For the MGInf queue, which service time distribution is a member of that collection, the busy period and busy cycle probabilistic studies are performed. In extra, the properties of that distributions collection are deduced and presented.
The purpose of the research is to study the renewal of the spatial and territorial environment of a city using the example of Barnaul. The key point of urbanized urban space is the concept of greening, since it is the most important component of the sphere of housing and communal services.
The objectives of the urban greening system are to create healthy, appropriate and favorable living conditions for the urban population, so the conceptual methodology will serve to calculate greening standards and the system of criteria for selecting green spaces. The comparative analysis of expert opinions on this relevant issue and the study of the cases of other Russian cities enable the co-authors to devise a method for calculating greening standards. Measures to improve the landscaping system in cities can be developed through the analysis of the current situation in the main sub-sectors of landscaping. In the future, this will allow us to design an "efficient" and, most importantly, socially-oriented urban space.The issues of creating, preserving and improving the quality of green areas are relevant not only for the municipality, or the city of Barnaul, but also for each urban settlement of the Russian Federation. Intensified activities, abundant information, and a high pace of urban life lead to constant overstrain among city residents. In this regard, the presence of a well-groomed urban forest, landscaped parks, and ennobled river banks is of great importance. Currently, their condition is of concern to urban residents and there is a need to clean garbage, reconstruct the green zone, create reservoirs, make new alleys, restore fountains, clean the banks of urban rivers.
At the current stage, development of economic relations is characterized by high competition in all sectors of economy with no exception. Requirements, applicable to the quality of products and services, resource conservation, environmental safety of products and technologies are increasing. Hence, these changes need investments and a balanced approach to the implementation of projects, having versatile foci and scale. In this regard, a portfolio management toolkit is increasingly used, since it allows for an optimal set of portfolio components and a clear focus on strategic changes in the company's activities. The portfolio management motivation is the ability to optimize investment resources and set disbursement priorities.
Given the strategic focus of the project portfolio, it is necessary to implement such processes as the assessment of each project from the standpoint of compliance with corporate strategic objectives, elimination of task duplication within the portfolio, cost and feasibility assessment, as well as project ranking and balancing. Many researchers believe that it is advisable to use expert analysis methods for the project selection and ranking, since experts are able to assess not only the quantitative, but also the qualitative characteristics of components, their strategic focus, and use extra data. The most acceptable methods are the analytic hierarchy process, the strategic buckets method.
Given that each project portfolio component has been examined and selected according to the commercial efficiency criteria, it is necessary to solve the task of assessing each component’s impact on the targets of the portfolio as a whole. We believe that the problem of developing a system of target indicators, related to the company activities, requires further consideration. To generate the project portfolio objective, it is advisable to apply the SMART methodology, which is focused on such characteristics of objectives as being specific, measurable, achievable, relevant for the company, and time-bound. This approach is quite consistent with the strategic focus of the project portfolio. The dynamic nature of the project portfolio implementation, along with the permanency of the strategic objectives, requires balancing the portfolio not only at the verification stage, but also at each life cycle phase, which will allow to avoid risks.
This paper aims to review and summarize approaches, goals and principles of a strategic project portfolio management in an organization, develop suggestions for ranking projects in the portfolio taking into account the interdependence of projects, the ability to implement strategic changes. Having focused on the standard project classification, the co-authors propose a step-by-step approach to the formation of an optimal set of the project portfolio components, providing systemic synergy. The co-authors propose a system of targets for ranking the project portfolio components to be based on the provisions of the portfolio management methodology and the experience of its implementation in various spheres of economy, regulatory legal acts, and opinions of well-known economists. The proposed project portfolio criteria are consistent with the requirements of the SMART goal setting methodology and include the following positions: revenue increase; production costs decrease; market share growth; the company's market capitalization growth. The rating of the portfolio component is determined by the sum of the contribution points to the achievement of the above targets.
The purpose of this study is to examine the role of the liquidity ratio, asset structure andbusiness risk in influencing the determination of capital structure. Property and real estate companies on the Indonesia Stock Exchange in 2016-2018 were employed as the research population, and obtained 39 companies as research samples. This study uses multiple linear regression analysis for hypothesis testing. The results of this study validate prior studies that test liquidity, asset structure and business risk, where liquidity and asset structure have an influence on the determination of capital structure. These results, especially in the asset structure proved consistent, although in this study the asset structure was considered from the point of view of the company's ability to manage current assets and fixed assets as determinants of capital structure. However, this study failed to prove that business risk can affect the capital structure.
Keywords: Liquidity, Asset Structure, Business Risk,and Capital Structure