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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.

Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

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 two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

The authors characterize the conditions under which a country may eventually split and when it splits within an infinite horizon multi-stage differential game.

In contrast to the existing literature, the authors do not assume that after splitting, players will adopt Markovian strategies. Instead, the authors assume that while the splitting country plays Markovian, the remaining coalition remains committed to the collective control of pollution and plays open-loop.

Within a full linear-quadratic model, the authors characterize the optimal strategies. The authors later compare with the outcomes of the case where the splitting country and the remaining coalition play both Markovian. The authors highlight several interesting results in terms of the implications for long-term pollution levels and the duration of coalitions under heterogenous strategies as compared to Markovian behavior.

In this paper, the authors have illustrated the richness of the simplications of enlarging the set of strategies in terms of the emergence of coalitions, their duration and the implied welfare levels per player. Varying only three parameters (the technological gap, pollution damage and coalition payoff share distribution across players), the authors have been able to generate, among other findings, quite different rankings of welfare per player depending on whether the remaining coalitions after split play Markovian or stay precommited to the pre-splitting period decisions.

This article is about reference books that can answer questions about the typical weather for a city in the United States or the actual weather on a given day in the past.