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The purpose of this paper is to understand how illusion of control (IOC) can affect the implementation of formal processes of environmental scanning in organizations.

Based on the proposed research question, an exploratory study was chosen, which could collaborate with future studies. There were conducted three semi-structured interviews with CEOs working in medium/large technology companies.

Behavioral traits were identified—such as overconfidence and underestimation of risks—which are directly related to the IOC’s theory. The belief that there is no added value to the company in adopting organizational strategic processes—such as environmental scanning—answers the research question and contributes to the development of new studies.

This study has as limitation the fact that it proposed the interviews to an inexpressive number of respondents, exclusively with the intention to explore better the relation between the IOC and the formal processes of environmental scanning.

This research advances the understanding of the difficulty in adopting formal environmental scanning practices in organizations. It can also help understand the motivations of executives for adopting (or not adopting) such practices. Finally, it is possible to know and understand the individual approach to environmental scanning, as well as its limitations.

This research discusses the themes of IOC and environmental scanning, demonstrating how cognitive factors can affect strategic decision making in an organization. Although the IOC is well-developed in the field of psychology, it can be very helpful in understanding business management and executive behavior.

Confidence intervals play a crucial role in economics and finance, providing a credible range of values for an unknown parameter along with a corresponding level of certainty. Their applications encompass economic forecasting, market research, financial forecasting, econometric analysis, policy analysis, financial reporting, investment decision-making, credit risk assessment and consumer confidence surveys. Signal-to-noise ratio (SNR) finds applications in economics and finance across various domains such as economic forecasting, financial modeling, market analysis and risk assessment. A high SNR indicates a robust and dependable signal, simplifying the process of making well-informed decisions. On the other hand, a low SNR indicates a weak signal that could be obscured by noise, so decision-making procedures need to take this into serious consideration. This research focuses on the development of confidence intervals for functions derived from the SNR and explores their application in the fields of economics and finance.

The construction of the confidence intervals involved the application of various methodologies. For the SNR, confidence intervals were formed using the generalized confidence interval (GCI), large sample and Bayesian approaches. The difference between SNRs was estimated through the GCI, large sample, method of variance estimates recovery (MOVER), parametric bootstrap and Bayesian approaches. Additionally, confidence intervals for the common SNR were constructed using the GCI, adjusted MOVER, computational and Bayesian approaches. The performance of these confidence intervals was assessed using coverage probability and average length, evaluated through Monte Carlo simulation.

The GCI approach demonstrated superior performance over other approaches in terms of both coverage probability and average length for the SNR and the difference between SNRs. Hence, employing the GCI approach is advised for constructing confidence intervals for these parameters. As for the common SNR, the Bayesian approach exhibited the shortest average length. Consequently, the Bayesian approach is recommended for constructing confidence intervals for the common SNR.

This research presents confidence intervals for functions of the SNR to assess SNR estimation in the fields of economics and finance.

Inspired by new findings on and perceptions of risk governance, such as the necessity of taking a broader perspective in coping with risks in companies and working together in interactive groups with various stakeholders to deal with complex risks in the modern world, the purpose of this paper is looking for new ways to deal with financial risks. Current methods dealing with those risks are confronted with the problems of being primarily based on past data and experience, neglecting the need for objectivity, focusing on the short-term future and disregarding the interconnectedness of different financial risk categories.

A literature review of risk governance, financial risk management and open foresight was executed to conceptualize solutions to the mentioned-above problems.

Collaborative financial risk assessment (CFRA) is a promising approach in financial risk governance with respect to overcoming said problems. It is a method of risk identification and assessment, which combines aspects of “open foresight” and the financial risk management and governance literature. CFRA is characterized as bringing together members of different companies in trying to detect weak signals and trends to gain knowledge about the future, which helps companies to reduce financial risks and increase the chance of gaining economic value. By overcoming organizational boundaries, individual companies may gain the knowledge they would probably not have without CFRA and achieve a competitive advantage.

A conceptual paper like the one at hand wants empirical proof. Therefore, the authors developed a research agenda in the form of five propositions for further research.

This paper discusses the existing problems of financial risk identification and assessment methods. It contributes to the existing literature by proposing CFRA as a solution to those problems and adding a new perspective to financial risk governance.

The purpose of this study is to measure the predictive value of future scenarios prepared using horizon scanning. The future scenarios prepared at the initiative of the Japanese Government have had low predictive value. They have frequently failed to contribute to industrial development and caused social loss. Horizon scanning, which is a key methodology applied in foresight activities, has begun to be used in countries as part of their national innovation systems in lieu of conventional forecasting methods based on the assumption of technological innovation. Research was conducted to actually measure the predictive value of future scenarios prepared using horizon scanning.

An online survey in Japan was conducted on ordinary people’s attitudes. The questionnaires presented 20 scenarios regarding future society, which were created with the conventional method or horizon scanning method.

Survey results verified that horizon scanning-based scenarios provided significantly higher predictive value than scenarios prepared using conventional methods.

Implication 1: By eliminating bias in input data and perspectives adopted when considering scenarios, it may be expected that scenarios will be derived that have even higher “predictive value.” Implication 2: By setting the layers of anticipated outputs high and the fields broad, it may be expected that scenarios will be derived that have even greater “change.”

The relatively high rate for the predictive value of the horizon scanning method, more than 40%, validated in this study was significant.

Whilst the relationship between corporate social responsibility (CSR) and corporate financial performance has been well documented, CSR has rarely been studied from the perspective of corporate poverty alleviation. This study aims to test whether participation in targeted poverty alleviation (TPA) affects firms' market value and to explore how the magnitudes of market value vary in different CSR environments.

Based on recent Chinese TPA initiatives and on 108 TPA announcements of Chinese-listed firms from 2016 to 2020, this study adopts an event study method to investigate the impact of firm's TPA announcements on the firm's market value. Then, the authors construct a cross-sectional regression to analyse different CSR factors that may affect market reactions.

The results demonstrate that TPA announcements can increase a firm's overall market value. Additionally, the results show that TPA way and firm ownership significantly moderate the market reaction, namely the positive reaction is more significant when the TPA announcements involve charity poverty alleviation rather than industrial poverty alleviation and for privately owned firms rather than state-owned firms.

The empirical results help TPA practitioners obtain a nuanced understanding of whether and when to participate in poverty alleviation is worthwhile. This study also provides a reference for poverty alleviation work in countries with similar backgrounds.

This study not only provides empirical evidence for the consequences of poverty alleviation behaviour of firms in developing countries, but also complements the field of CSR research in developed countries.

The purpose of this research work is to examine the financial effect of supply chain disruptions (SCDs) caused by coronavirus disease 2019 (COVID-19) and how the magnitude of such effects depends on event time and space that may moderate the signaling environment for shareholder behaviors during the pandemic.

This study analyses a sample of 206 SCD events attributed to COVID-19 made by 145 publicly traded firms headquartered in 21 countries for a period between 2020 and 2021. Change in shareholder value is estimated by employing a multi-country event study, followed by estimating the differential effect of SCDs due to the pandemic by event time and space.

On average, SCDs due to pandemic decrease shareholder value by −2.16%, which is similar to that of pre-pandemic SCDs (88 events for 2018–2019). This negative market reaction remains unchanged regardless of whether stringency measures of the firm's country become more severe. Supply-side disruptions like shutdowns result in a more negative stock market reaction than demand-side disruptions like price hikes. To shareholder value, firm's upstream or downstream position does not matter, but supply chain complexity serves as a positive signal.

This study provides the first empirical evidence on the financial impact of SCDs induced by COVID-19. Combining with signaling theory and event system theory, this study provides a new boundary condition that explains the impact mechanism of SCDs caused by the pandemic.

This paper aims to examine the strategy, selection and perception of facility management (FM) services and the effect it may have on perceived building quality.

Data was collected through a survey distributed to board members of cooperatives for newly constructed buildings in Sweden. Responses from 394 cooperative boards were included in the data set and analysed. The difference in cooperative choice of FM strategy and satisfaction with FM services was examined with non-parametrical Kruskal–Wallis tests and the effect of FM strategy and satisfaction with FM services on perceived building quality was examined with a one-way analysis of variance (ANOVA) test.

The results suggest information asymmetry and indicate urgent need for an objective accreditation system for FM services, which will inform and assist housing owners in the FM selection process. The study validates the hypothesis that facilities management strategies applied by housing cooperatives have a significant effect on perception of building quality.

The findings will assist developers, facility and property managers to understand the needs and services valued by the housing cooperative. The findings highlight the information asymmetry, restricted techniques and weak signalling methods among FM services, and advocates promoting an objective accreditation system for FM services.

The study contributes to the discussion on the concept of building quality and the results presented provide a better understanding of facilities management strategy on perception of building quality.

This study aimed to evaluate the impact of four cross-institutional teaching enhancement projects (TEPs), a relatively new form of professional collaboration. The focus is on the impact at departmental, institutional and cross-institutional levels because such impact is the main reason for establishing cross-institutional TEPs.

A professional capital framework guided the examination of decisional and social capitals at departmental, institutional and cross-institutional levels. A theory-of-change method was adopted to collect data from 35 sets of documents, 22 project members and 65 stakeholders.

The authors found five forms of impact, showing the development of decisional and social capitals mostly at institutional and cross-institutional levels, whilst signaling the relatively weak impact at departmental levels. Therefore, the values of cross-institutional TEPs have not been fully realized and future endeavors need to better utilize the capitals in programs.

Few studies evaluated the impact of large-scale, cross-institutional TEPs. The authors offered new contributions by gauging the impact of these under-explored forms of complex professional collaborations.