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This study evaluates the Federal Reserve (Fed) initial and final forecasts of the unemployment rate for 1983Q1-2018Q4. The Fed initial forecasts in a typical quarter are made in the first month (or immediately after), and the final forecasts are made in the third month of the quarter. The analysis also includes the private forecasts, which are made close to the end of the second month of the quarter.

In evaluating the multi-period forecasts, the study tests for systematic bias, directional accuracy, symmetric loss, equal forecast accuracy, encompassing and orthogonality. For every test equation, it employs the Newey–West procedure in order to obtain the standard errors corrected for both heteroscedasticity and inherent serial correlation.

Both Fed and private forecasts beat the naïve benchmark and predict directional change under symmetric loss. Fed final forecasts are more accurate than initial forecasts, meaning that predictive accuracy improves as more information becomes available. The private and Fed final forecasts contain distinct predictive information, but the latter produces significantly lower mean squared errors. The results are mixed when the study compares the private with the Fed initial forecasts. Additional results indicate that Fed (private) forecast errors are (are not) orthogonal to changes in consumer expectations about future unemployment. As such, consumer expectations can potentially help improve the accuracy of private forecasts.

Unlike many other studies, this study focuses on the unemployment rate, since it is an important indicator of the social cost of business cycles, and thus its forecasts are of special interest to policymakers, politicians and social scientists. Accurate unemployment rate forecasts, in particular, are essential for policymakers to design an optimal macroeconomic policy.

Despite the plethora of research into country-of-origin (COO) effects, research that investigates the cognitive structures behind elite consumers' preferences for foreign brands remains limited. Hence, this study aims to investigate the cognitive structures behind foreign brand preference among professional elites in Sri Lanka.

Using the means-end chain (MEC) theory as the theoretical lens and building on the findings of 30 laddering interviews (semi-structured), a survey was conducted among 311 professional elites to uncover the key elements of the cognitive structures behind foreign brand preference.

The findings revealed that the cognitive structures behind foreign brand preference are influenced by a bundle of brand attributes, brand consequences and personal values of elites', which significantly influence their attitudes towards foreign brands. Multi-group analysis further revealed that the relationship between brand attributes and attitudes significantly differs across Chinese and US COOs where the path coefficient is stronger for elites' preference for Chinese brands.

This study is the first of its kind to explore the COO effects on consumer cognitive structures. The findings contribute to MEC theory and shed light on the understanding towards elites' preference for foreign brands.

Digital transformation (DT) is among the vital factors contributing to innovation ambidexterity, especially for advanced manufacturing firms (AMFs). However, the empirical studies on the relationship between DT and innovation ambidexterity in AMFs from the perspective of knowledge management are inadequate. Therefore, this study aims to systematically analyze the impact of DT on innovation ambidexterity and its mechanism of action.

This study selects 254 listed firms within the ten key areas of “Made in China 2025,” as they occupy a key position in China’s advanced manufacturing system. Based on the knowledge-based view (KBV) and contingency theory, it constructs a model of the influence mechanism of DT on innovation ambidexterity.

The results show that the DT of AMFs positively influence innovation ambidexterity. External pressure from environmental turbulence enhances the positive relationship between DT and innovation ambidexterity, demonstrating the “resilience effect,” external knowledge search (EKS) and broadening the knowledge base mediating roles between them, highlighting the “accumulation effect.”

By identifying this mediation mechanism of DT and innovation ambidexterity, this study provides new ideas for path research on the KBV. Moreover, this study explores the triggering effect of market environmental turbulence on the DT of firms. It reveals the boundary conditions of DT acting on innovation ambidexterity, expands the research perspective on organizational resilience and enriches the theory of power change.

For almost half a century, society has been aware of the existence of a glass ceiling, a term that describes the invisible barriers that hinder women’s access to power positions despite having equal or greater qualifications, skills and merits than their male counterparts. Nowadays, although there are signs of slow progress, women are still underrepresented in the upper echelons of large corporations and the risk of reversing the progress made in gender parity has increased because of the effects of the COVID-19 pandemic. This paper contributes to previous literature by analysing the impact that the uncertainty and cognitive effects associated with COVID-19 in 2020 had on the presence of women on the board of directors and whether this impact has been moderated by the regulatory and policy system on gender quotas in place at the time.

To test the authors' research hypotheses, the authors selected the major global companies worldwide with economic-financial and non-financial information available in the Thomson Reuters EIKON database over the 2015–2020 period. As a result, the authors' final sample is made up of 1,761 companies from 52 countries with different institutional settings that constitute an unbalanced data panel of 8,963 observations. The nature of the dependent variables requires the use of logistic regressions. The models incorporate the terms to control for any unobservable heterogeneity and the error term. Any endogeneity issues were addressed by considering the explanatory variables with a time lag.

The authors find that almost 30% of the companies downsized their boards in 2020. This decision resulted in more female than male directors being made redundant, causing a reversal in the fulfilment of gender quotas focussed on ensuring balanced boards with a female presence of 40% or more. This effect was enhanced in countries with hard-law regulation because the penalty for non-compliance with gender quotas had led to a significant increase in the size of these bodies in previous years through the inclusion of the required number of female directors. In contrast, the reduction in board size in soft-law countries does not differ from that in laissez-faire countries, lacking any moderating effect or impact on the number of female board members dismissed as a result of the pandemic.

This paper aims to contribute to current knowledge by analysing the impact that the countries' regulatory and normative systems on gender parity on boards of directors have had on the decisions made in relation to leadership positions, moderating the effects of the COVID-19 pandemic on gender equality at a global level.

It is important to note that insider trading is currently outlawed under the Securities Act 17 of 2004 (Chapter 24: 25) as amended (Securities Act) in Zimbabwe. This Act enumerates some practices that may give rise to insider trading liability in the Zimbabwean financial markets. Nonetheless, numerous challenges, such as the lack of adequate financial resources, the lack of sufficient persons with the relevant skills and expertise on the part of the enforcement authorities, lack of political will, inadequacy of insider trading provisions, poor cooperation and collaboration between the relevant authorities and the ongoing coronavirus (Covid-19) pandemic have negatively impeded the effective regulation and combating of insider trading in Zimbabwe. To this end, the author explores the stated challenges and recommend measures that could be used by regulatory bodies and other relevant enforcement authorities to enhance the regulation and combating of insider trading in the Zimbabwean financial markets. This study aims to enhance the detection and combating of insider trading in Zimbabwe.

A qualitative research methodology is used through the analysis of relevant legislation and case law.

It is hoped that the findings and recommendations made in this study will be considered by the Zimbabwean policymakers.

The study does not use empirical research methodology.

The findings and recommendations made in this study could enhance the combating of insider trading activities in Zimbabwe.

The study seeks to curb insider trading in the Zimbabwean financial markets and financial institutions in the wake of the covid-19 pandemic-related regulatory and enforcement challenges.

The study provides original research on the regulation and combating of insider trading activities in Zimbabwe.

This article aims to elaborate the context-sensitive nature of credibility assessment by examining how such judgments are made in online discussion in times of uncertainty caused by Finland's intent to join the North Atlantic Treaty Organization (NATO) in spring 2022.

The empirical findings draw on the qualitative content analysis of 3,324 posts submitted to a Finnish online discussion in February–March 2022. It was examined how the participants of online discussion assess the credibility of information sources referred to in debates on the NATO membership. It is assumed that the believability of the author of information is indicative of his or her expert power, for example based on the credentials of a scholar, while the credibility of information content, for example the provision of factual evidence is indicative of the source's informational power.

Political decision-makers, particularly the President of Finland were assessed as most credible information sources, due to their access to confidential knowledge and long-time experience in politics. The credibility assessments differed more strongly while judging the believability of researchers. On the one hand, their expertise was praised; on the other hand, doubts were presented about their partiality. Fellow participants of online discussion were assessed most negatively because information sources of these types are associated with low expert and informational power.

As the study concentrated on credibility assessments made in a Finnish online discussion group, the findings cannot be extended to concern the credibility judgments occurring information in other contexts.

The study is among the first to characterize the role of expert and informational power in credibility assessment in times of uncertainty.

The Sendai framework for disaster risk reduction (DRR) 2015–2030 offers guidelines to reduce disaster losses and further delivers a wake-up call to be conscious of disasters. Its four priorities hinge on science, technology and innovations as critical elements necessary to support the understanding of disasters and the alternatives to countermeasures. However, the changing dynamics of current and new risks highlight the need for existing approaches to keep pace with these changes. This is further relevant as the timeline for the framework enters its mid-point since its inception. Hence, this study reflects on the aspirations of the Sendai framework for DRR through a review of activities conducted in the past years under science, technology and innovations.

Multidimensional secondary datasets are collected and reviewed to give a general insight into the DRR activities of governments and other related agencies over the past years with case examples. The results are then discussed in the context of new global risks and technological advancement.

It becomes evident that GIS and remote sensing embedded technologies are spearheading innovations for DRR across many countries. However, the severity of the Covid-19 pandemic has accelerated innovations that use artificial intelligence-based technologies in diverse ways and has thus become important to risk management. These notwithstanding, the incorporation of science, technology and innovations in DRR faces many challenges. To mitigate some of the challenges, the study proposes reforms to the scope and application of science and technology for DRR, as well as suggests a new framework for risk reduction that harnesses stakeholder collaborations and resource mobilizations.

The approach and proposals made in this study are made in reference to known workable processes and procedures with proven successes. However, contextual differences may affect the suggested approaches.

The study provides alternatives to risk reduction approaches that hinge on practically tested procedures that harness inclusivity attributes deemed significant to the Sendai framework for DRR 2015–2030.

Although real estate investment decisions are among the most important managerial decisions, such decisions are usually made in an ad hoc fashion in Southeast Asia. The purpose of this study is to present a two-tier multi-criteria decision-making model for real estate investment decisions across three rapidly growing but significantly understudied Southeast Asian countries: Cambodia, Myanmar and Vietnam.

Using three data sources (secondary data, two surveys and nearly 100 experts and senior executives), the authors applied a combination of the Analytic Hierarchy Process and the Simple Additive Weighting (or weighted sum) methods as two special cases of multi-criteria decision-making to assess nine real estate investment projects across Cambodia, Myanmar and Vietnam.

The results of this study indicated that Vietnam, Cambodia and Myanmar were the first, second and third most preferred countries for real estate investments, respectively. Moreover, the results clearly show a trade-off between perceived country risk and financial returns, indicating that a higher perceived country risk can be compensated for with higher financial returns.

Real estate investment decisions are usually made in an ad hoc manner in Southeast Asia. This study helps investors make more informed decisions when investing in real estate projects across three rapidly growing but significantly understudied Southeast Asian countries: Cambodia, Myanmar and Vietnam.

The purpose of this paper is to examine the contribution that problem structuring methods – a branch of the decision support discipline of operational research – have made in helping managers deal with situations of high complexity. The paper reviews the limitations of traditional operational research and argues that problem structuring methods have expanded the entire discipline and significantly contributed to its holistic nature and problem-solving orientation.

The paper provides a critical discussion of the limitations of the traditional operational research approach and examines how the development and successful application of problem structuring methods have opened up a new paradigm of analysis in management science.

In theoretical terms, problem structuring methods have moved the discipline of operational research away from its positivistic epistemology and towards interpretivism and the acceptance of a subjective social reality. In practical terms, they offer managers a broad range of appropriate analytical tools which provide transparency and offer the opportunity to those affected by the problem situation to be actively involved in the entire modelling process within a facilitated environment.

The paper offers a critical discussion of the contribution that problem structuring methods have made while also identifying the challenges they face as they try to achieve higher levels of recognition and acceptance in management science.

The versatility of customer relationship management (CRM) systems has kept these technologies popular over the years. These solutions have been integrated into organizations of all sizes, from large corporations to small- and medium-sized enterprises. Similarly, CRM systems have also found applications in all types of industries and business sectors. All this has been the driving force behind the proliferation of CRM solutions around the world. In this chapter, the author not only reflects on the impact and democratization of CRM systems on business management and marketing strategies but also explores how these technologies can determine the company's income. In particular, the author presents an experiment that analyzes the extent to which the volume of annual investment in CRM solutions can be used to predict annual net income in a sample of companies. Using time series analysis and applying the autoregressive integrated moving average modeling technique, the researcher examines a sample of 10 companies from different industries, and countries, over a 20-year period. The results show the efficiency of the predictive models developed in nine of the 10 companies analyzed. The findings of this study allow us to conclude that there seems to be an association between the investments made in CRM solutions and the income of the companies that invest in these technologies.