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Purpose: The purpose of the work is to study the essence and to determine the algorithm and methodology of decision making as a choice of the existing alternatives according to the scientific approach to this process of management of modern business systems.

Methodology: The research is conducted with the help of the method of process analysis, which allows determining the stages of the process of decision making in modern business systems and determining its algorithm; the method of formalization, which allows presenting the obtained algorithm; and the method of comparative analysis, which allows comparing the existing methods of decision making as a choice of the existing alternatives.

Conclusions: As a result of generalization and systematization of the existing scientific knowledge in the sphere of managerial decisions in modern business systems and reconsideration (logical analysis) of this process, its algorithm is compiled. Four stages of the algorithm of making of managerial decisions in modern business systems are distinguished – determining the needs of business system for managerial decisions, determining the possibilities of business system in making of managerial decisions, compiling alternative variants of managerial decisions, and implementation of the made managerial decision and further evaluation of its optimality. Also, methodological tools of each stage are determined.

Originality/value: The developed algorithm possesses the following advantages as compared to the existing scientific descriptions of this process: completeness, complex solution of the problems of the business system through managerial decisions, connection of the methodology of managerial decisions to each stage of the algorithm, and systemic character of the methodology of decision making as a choice of the existing alternatives.

Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically.

Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio.

Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks.

Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model.

Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks.

The purpose of the research is to determine the signs of nonoptimality of managerial decisions that are made by Russian business systems and to determine the barriers on the path of making of optimal decisions in business systems by the example of modern Russia and perspectives of overcoming them.

The information and empirical basis of the research consists of statistical materials of the World Economic Forum, RIA Rating and Samuel Centre for Social Connectedness for 2018, according to which signs of nonoptimality of managerial decisions of Russian business systems, which are observed at the macro-level, are determined. During the research, the method of systemic, problem, and logical analysis (analysis of causal connections) and the method of formalization are used.

It is determined that drawbacks of the process of making of managerial decisions in modern Russian model of this process, connected to the functional organizational structure, low marketing activity, and underdevelopment of internal business communications, create barriers on the path of making of optimal decisions: high expenditures for making of managerial decisions, duration of the process of making of managerial decisions, high complexity of choice of alternative decisions, and incomplete accounting of possibilities and problems during decision-making.

Perspectives of overcoming the determined barriers are connected to the usage of outsource during the making of managerial decisions, refusal from functional organizational structure of managerial staff, usage of means of authomatization of making of managerial decisions, and development of systemic feedback and marketing. According to the studied practical experience of the largest and well-known Russian business systems – Rosneft, Lukoil, Gazprom, and Sberbank – these perspectives (2018) are not implemented in Russia.

This chapter analyses the efficiency of African airlines using a two-stage network DEA (Data Envelopment Analysis) model. Network DEA models usually take into account the production process with intermediate inputs derived from the first stage and a second stage that departs from it. This fundamental feature enables one to view the airline production process as a carry-over activity. The analysis covers the 2010–2013 period. The relative efficiency ranks are presented and policy implications are derived.

The Association of Southeast Asian Nations (ASEAN) members want to efficiently promote the flow of commodities and personnel within its service areas under given limited resources. Based on panel data from 2007 to 2014, this study applies the output-oriented data envelopment analysis method and focuses on the disaggregated output efficiencies of 42 ASEAN airports. Results show that the international airports of ASEAN members have significantly better output efficiency for passenger and movement output than regional airports. This work provides a relatively fair perspective in evaluating ASEAN’s airport operating efficiency. It helps policymakers measure the frontier forward or backward shift of an airport over the research period, in order to reveal the characteristics of airport efficiency and to present a new interpretation along with managerial implications.

To address management issues in the development of flexible production systems in the enterprises of knowledge-intensive industries, this chapter considers four basic approaches to planning production processes. Based on these approaches, the methodology of the agent-based approach, which satisfies the fundamental requirements of today's production systems, is formulated, with much attention paid to the rules of dispatching as a key tool of operational control over the production plan and its implementation. The advantage of simulation-based approaches is that they can dynamically adjust the ongoing integration of planning, depending on the state of flexible production systems, in the use of combined approaches and methods of management of production processes.

The authors construct an intertemporal model of rent-maximizing behavior on the part of a timber harvester under potentially multidimensional risk as well as geographical heterogeneity. Subsequently, the authors use recursive methods (specifically, the method of stochastic dynamic programing) to characterize the optimal policy function – the rent-maximizing timber-harvesting profile. One noteworthy feature of their application to forestry in the province of British Columbia, Canada is the unique and detailed information the authors have organized in the form of a dynamic geographic information system to account for site-specific cost heterogeneity in harvesting and transportation, as well as uneven-aged stand dynamics in timber growth and yield across space and time in the presence of stochastic lumber prices. Their framework is a powerful tool with which to conduct policy analysis at scale.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

This paper advances the specification and estimation of econometric models of retirement and saving in two earner families. The complications introduced by the interaction of retirement decisions by husbands and wives have led researchers to adopt a number of simplifications. Our analysis relaxes these restrictions. The model includes three labor market states, full-time work, partial retirement, and full retirement; reverse flows from states of lesser to greater work; an extended choice set created when spouses make independent retirement decisions; heterogeneity in time preference; varying taste parameters for full-time and part-time work; and the possibility of changes in preferences after retirement.

Empirical studies show that years of schooling are positively correlated with good health. The implication may go from education to health, from health to education, or from factors that influence both variables. We formalize a model that determines an individual’s demand for knowledge and health based on the causal effects, and study the impacts on the individual’s decisions of policy instruments such as subsidies on medical care, subsidizing schooling, income tax reduction, lump-sum transfers, and improving health at young age. Our results indicate that income redistribution policies may be the best instrument to improve welfare, while a medical care subsidy is the best instrument for longevity. Subsidies to medical care or education would require large imperfections in these markets to be more welfare improving than distributional policies.