Strategic Management - International Journal of Strategic Management and Decision Support Systems in Strategic Management

Uncertainty decomposed: understanding levels of contingency to enable effective decision-making

2023-09-18T21:24:39+02:00

Background: Uncertainty is a common challenge in managerial decision-making, especially when it comes to predicting future states, establishing cause-effect relationships, and having knowledge about relevant variables. However, it is difficult to deliberately address different types of uncertainty by applying specific decision-making strategies and hence enable reduction of uncertainty due to overlapping definitions and conflicting operationalization of the uncertainty construct.

Purpose: The paper aims to delineate types of uncertainty along their epistemological configurations in terms of specific knowledge contexts to enable choices of suitable strategies for specific decision-making situations.

Study design/methodology/approach: A literature review revises and discusses concepts of (un)certainty based on (im)perfect information and objectively/subjectively available assemblages of knowledge.

Findings/conclusions: The paper provides a framework that encompasses and differentiates configurations of available information and knowledge applicable to decision-making situations. In order to achieve construct clarity and to free the original concept of uncertainty from conflicting definitions and heterogeneous operationalizations, the umbrella term contingency is introduced. It encompasses all states of (im)perfect information and variations in their epistemological configurations. Finally, the presented epistemological framework delineates levels of contingency along specific qualities of available information. The identified and discussed levels of contingency are certainty, risk, uncertainty in the narrow sense (i.n.s.), complexity, ambiguity/equivocality, and isotropy/radical uncertainty. The delineated levels of contingency help to tailor decision-making situation to specific epistemological configurations and hence may serve as a starting point for concluding and developing appropriate strategies to reduce contingency.

Limitations/future research: A holistic understanding how to deal with and solve contingency requires further research focusing on aligning levels of contingency with strategies for decision-making (algorithms, causation, effectuation, bricolage, improvisation, trial & error) by taking types of knowledge (structural, procedural, conceptual) and contextual factors (e.g. time, [origin of] resources) into account.

Determining the investors’ strategy during the COVID-19 crisis based on the S&P 500 stock index

2022-09-12T07:05:14+02:00

Background: The most significant changes caused by the COVID-19 crisis were the sharp increase in working from home and the growing importance of e-commerce, which affected the development of some industries. This change also affects the investors' investment operations, which are based on analysis to ensure an unquestionable certainty of the invested financial amount and a satisfactory return. It is, therefore, interesting to analyze the possible return of the chosen investment strategy based on the optimization model of portfolio selection based on the CVaR risk measure.

Purpose: The paper aims to present the possible use of the analysis of returns of effective portfolios constructed based on the optimization model of portfolio selection based on the CVaR risk measure during the crisis (COVID-19) and the pre-crisis period.

Study design/methodology/approach: Paper presents the impact of the COVID-19 crisis on investor decision-making through the CVaR risk measure, which was implemented on the historical data of the components of the Standard and Poor's 500 stock index (S&P 500) in the crisis period as well as in the pre-crisis period.

Findings/conclusions: The presented approach based on the CVaR risk rate measure and the relevant portfolio selection model provides the investor with an effective tool for allocating funds to the financial market in particular segments in both monitored periods.

Limitations/future research: Time series data are divided into two periods based on visible factors such as the number of COVID-19 cases. In future research, we aim to divide monitored periods based on unobservable factors influencing investors' decisions, such as bull or bear mood on the market.

Assessing sustainable economic development efficiency: a DEA approach

2022-11-15T13:17:18+01:00

Background: Widely used in efficiency analysis, data envelopment analysis (DEA) found its use in country efficiency measurement concerning the achievement of desired values of macroeconomic indicators, most often the goals from the category of economic growth.

Purpose: The objective of the paper is to examine the possibility of DEA application in sustainable development research.

Methodology: The analysis was conducted using a non-oriented DEA model with variable return-to-scale in a group of 26 EU countries and Serbia, as a membership candidate. Four variables were used as input variables: inflation rate, unemployment rate, poverty rate and ecological footprint per capita. Three variables were used on the outputs side: inequality-adjusted human development index, GDP per capita and ecological deficit or reserve per capita. The annual data was collected for the time period of eight years, form 2010 until 2017.

Findings: Results show that Finland is the only country efficient throughout the entire period. Average efficiency close to maximum was achieved by the Netherlands. Significant efficiency was achieved by Luxembourg, Germany and Sweden among countries that were EU members before 1995. Among other EU countries, Slovenia and Hungary achieved efficiency on a nearly maximum level. Also, efficient in more than half of the observed years were Cyprus and Romania. The most inefficient countries were the three Baltic countries: Lithuania, Latvia, and Estonia. Among the EU member countries before 1995, Italy and Portugal were the most inefficient. Concerning EU candidate Serbia, the efficiency achieved was generally close to average.

Limitations: The performed analysis can answer the question of which country is the most efficient on the way to sustainability. However, the DEA method cannot show whether a country is developing absolutely sustainably or unsustainably, because DEA is a relative method and can only measure efficiency compared to the other units.

The impact of motivation to decision on digital transformation of social entrepreneurship

2023-09-05T14:05:18+02:00

Background: Today, the digital transformation of business is one of the conditions for survival on the market. The development of digital technology is progressing rapidly, and only the business entities that keep pace with this development can expect good business results. Social entrepreneurship is an excellent way to solve the problems of social inequality and poverty and thus leads to economic growth and development.

Purpose: The main goal of this research is to create a theoretical model of digital transformation of social entrepreneurship. This model can be a useful tool for deciding on the digital transformation of business. We investigated motivation of managers and employees as an influencing factor for the digital transformation of business. We declared other influencing factors as constants.

Study design: We measured motivation by personal and professional use of the Internet, the acquisition of digital skills, the cost of labour of those who are involved in the digitisation process, and the application of data protection software. Ninety-seven social entrepreneurship entities from Bosnia and Herzegovina (B&H) participated in the research. The research was carried out using questionnaires, and we analysed the obtained data using correlation and regression methods.

Findings: The results showed that motivation is a significant factor in the digital transformation of social entrepreneurship. Based on the results of the research, we have created a model of digital transformation of social entrepreneurship entities that can lead to economic and social development through steps applicable in practice.

Limitations/future research: The most significant limitation of the research is the lack of an official register of social entrepreneurship entities from which we can collect data about the number of these entities. To future researchers, we leave open questions of other influencing factors for the development of social entrepreneurship, such as knowledge, sources of funding for initial business activities, etc.

Determinants of learning outcomes with online teaching based on students’ perception

2023-04-27T08:30:27+02:00

Background: Research on the topic of determining success of online learning is on the rise. Defining the key success factors, i.e. determinants of online learning success, is extremely important, especially at present as all higher education institutions have been forced to try their hand at teaching with the help of technology.

Purpose: Thus a research examining factors of learning outcomes of online learning was conducted. Learning outcomes were modelled as dependent variable, while the set of independent model variables included: course design, student motivation, student self-regulation and dialogue (instructor-student, student-student).

Study design/methodology/approach: Five research hypotheses were tested by analysing data collected from the students of the University of Novi Sad. A structured questionnaire was employed to collect data on the attitudes of users (students) to online learning. Respondents expressed their views (perception) about statements and valued them on a 5 point Likert scale. The instrument was applied to a sample of 360 responses using PLS structural equation modelling.

Findings/conclusions: All five hypothesis were supported with the analysis, confirming the importance of research from the aspect of contribution to the literature dedicated to identifying the key success factors of online learning. Additional contribution refers to the research conducted in Serbia, i.e. at the University of Novi Sad.

Limitations/future research: A more detailed analysis of the model itself and the possibility of finding the interdependence of constructs that affect perceived learning outcomes and user satisfaction remains as an area for further research.