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Investors’ fear can be rational, emanating from the natural dynamics of economic fundamentals, or it can be quasi rational and not attributable to any known risk factors. Using VIX from Chicago Board Options Exchange as a proxy for investors’ fear, the purpose of this paper is to consider the following research questions: to what extent does noise play a role in the formation of investors’ fear? To what extent is the impact of fear on S&P 500 index returns driven by rational reactions to new information vs fear induced by noise in stock market returns? To what extent do S&P 500 index returns display asymmetric behavior in response to investor’s rational and quasi rational fear?

In a two-step process, the authors first decompose investors’ fear into its rational and irrational components by generating two additional variables representing fear induced by rational expectations and fear due to noise. The authors then estimate a three-vector autoregression (VAR) model to examine their relative impact on S&P 500 returns.

Impulse responses generated from a 13-variable VAR model show that investors’ fear is driven by risk factors to some extent, and this extent is well captured by the Fama and French three-factor and the Carhart four-factor models. Specifically, investors’ fear is negatively related to the market risk premium, negatively related to the premium between value and growth stocks, and positively related to momentum. The magnitude and duration of the impact of the market risk premium is almost twice that of the impact of the premium on value stocks and the momentum of investors’ fear. However, almost 90 percent of the movement in investors’ fear is not attributable to the 12 risk factors chosen in this study and thus may be largely irrational in nature. The impulse responses suggest that both rational and irrational fear have significant negative effects on market returns. Moreover, the effects are asymmetric on S&P 500 index returns wherein irrational upturns in fear have a greater impact than downturns. In addition, the component of investors’ fear driven by irrationality or noise has more than twice the impact on market returns in terms of magnitude and duration than the impact of the rational component of investors’ fear.

The results are consistent with the view that one of the most important drivers of stock market returns is irrational fear that is not rooted in economic fundamentals.

Early information technology scholarship centered on the internet’s potential to be a democratizing force was often framed using an equalization/normalization lens arguing that either the internet was going to be an equalizing force bringing power to the masses, or it was going to be normalized into the existing power structure. The purpose of this paper is to argue that considered over time the equalization/normalization lens still sheds light on our understanding of how social media (SM) strategy can shape electoral success asking if SM are an equalizing force balancing the resource gap between candidates or are being normalized into the modern campaign.

SM metrics and electoral data were collected for US congressional candidates in 2012 and 2016. A series of additive and interactive models are employed to test whether the effects of SM reach on electoral success are conditional on levels of campaign spending.

The results suggest that those candidates who spend more actually get more utility for their SM campaign than those who spend less in 2012. However, by 2016, spending inversely correlates with SM campaign utility.

The findings indicate that SM appeared to be normalizing into the modern congressional campaign in 2012. However, with higher rates of penetration and greater levels of usage in 2016, the SM campaign utility was not a result of higher spending. SM may be a greater equalizing force now.

Campaigns that initially integrate digital and traditional strategies increase the effectiveness of the SM campaign because the non-digital strategy both complements and draws attention to the SM campaign. However, by 2016 the SM campaign was not driven by its relation to traditional campaign spending.

This is the first large N study to examine the interactive effects of SM reach and campaign spending on electoral success.

Unlike the traditional growth model of emerging markets after economic liberalization, India’s inward foreign direct investment (FDI) surged paralleling its strong economic growth in the 2000s, despite the failure to establish a strong secondary sector. This creates an opportunity to deepen the conceptual and contextual understanding of the pivotal mechanisms that impel foreign multinational enterprises to invest into India and provides a natural setting to better understand the nature of its institutional, political and economic environment.

The authors develop a theory contextualized to Indian inward FDI patterns for the 2000–2017 period. The theoretical framework expands upon received investment motives, with explicit consideration given to the idiosyncrasies of developments in India’s recent macro and socioeconomic environment. The authors test the hypotheses using panel data from 134 countries that invested in India, using a Hausman–Taylor estimation.

The authors find that India’s transition toward a knowledge economy attracts asset augmenting rather than asset exploiting FDI. Investors appear to target long-term investments by gaining access to India’s digital capabilities, R&D, and growing talent base with a high degree of specialization within analytics, biotechnology, engineering, or pharmaceuticals. Foreign investors do not seem to be notably deterred by infrastructural challenges nor by legal and regulatory restrictions.

By providing a new perspective on India’s atheoretical economic development and FDI environment, this study offers a distinct point of comparison with regard to established hypotheses within the extant literature on FDI into emerging markets. Rethinking contemporary investment motive theory by introducing an adapted conceptual framework provides further opportunity to inform the understanding of firm strategies in similar environments.

COVID-19 has shaken views of what is normal and what is possible, raising questions about conventional norms, ways of working and our understanding of agility. This paper aims to respond to calls for empirical research of supply chain capacities in times of crisis and offer a unique perspective on agile procurement and supply chain management from a case study of the Ventilator Challenge.

A descriptive case study was undertaken, adopting an inductive approach. Interviews were conducted with the major stakeholders tasked with the design, sourcing and assembly of ventilators.

Findings are delivered across four key areas: context; procurement and supply chain management; technology and culture; and environment. Key challenges and enablers are discussed, highlighting the critical roles of trust, empowerment and enabling technologies in the construction of an entirely new ventilator supply chain, from scratch, in five weeks.

This paper delivers contributions for both academic research and practice. The case study offers rich new insights relating to procurement in times of crisis, contributing to efforts to advance beyond outdated approaches for resilience in literature. Practical contributions arise in highlighting the significance of adapted sourcing and recruitment, technology, collaboration, people and power of purpose in enabling agility and achieving the impossible.

The purpose of this paper is to determine whether features of next-generation Online Public Access Catalogue (OPAC) interfaces are useful and intuitive to users who have different levels of searching ability. In addition, it investigates whether there is a difference between librarians’ and students’ preferences for specific features.

The research is based on 18 semi-structured interviews conducted in July 2012 with three groups of library users from The University of Sheffield: librarians; Master of Arts Librarianship students; and a group of other post-graduate students.

Overall, this study suggests that while the next-generation catalogue interfaces and features are useful, they are not as “intuitive” as some previous studies have claimed. Interviewees appeared to prefer the searching and browsing options over the Web 2.0 features. Both librarians and students have similar opinions regarding the usefulness of next-generation OPAC features, but preferences are complex.

The study is based on one institution, and the disciplinary background of the post-graduate students was limited.

Promoting next generation OPACs and explaining their features to users is essential.

The paper adds to the understanding of users’ preferences in relation to next-generation OPACs, locating the findings of the current findings firmly in the context of previous literature.

The purpose of this paper is to contribute to the effectiveness of teaching in economics.

This paper provides as a case study, the authors’ reflections on a first-year “learning community” at a US liberal arts college, which combined courses on political science and economics to explore issues of political economy, including poverty and social mobility.

The authors argue that, compared with standard delivery, using literature allows increased student access to and, thus, greater engagement with certain theoretical concepts. More specifically, literature can open avenues for critical thought, and challenge pre-existing views, when it illuminates controversial questions without providing obvious answers. It is this open-ended aspect of literature that seems to provide the best opportunity for increased student engagement and critical thinking.

The arguments in this paper are based on authors’ reflections and would benefit from other empirical analysis. This method of teaching only offers pedagogical opportunities, and learning gains do not occur automatically. Several features of the course design and assessment, and the interaction between disciplines, made the use of literature more likely to be successful.

These authors also reflect more broadly on their use of literature in other courses, and provide some suggestions for specific works that might be used in further teaching and research.

This paper contributes to current debate on teaching practice in economics, and will be of use to those seeking to challenge student viewpoints in a subtle yet effective manner.

Based on the emerging view of supply chains as complex adaptive systems, this paper aims to build and test an analytical model for resilience assessment surrounding supply chain risks at the level of the supply chain system and its individual tiers.

To address the purpose of this study, a multimethod research approach is adopted as follows: first, data envelopment analysis (DEA) modelling and fuzzy set theory are used to build a fuzzy network DEA model to assess risk resilience of the overall supply chains and their individual tiers; next, the proposed model is tested using a survey of 150 middle- and top-level managers representing nine industry sectors in Iran.

The survey results show a substantial variation in resilience ratings between the overall supply chains characterizing nine industry sectors in Iran and their individual tiers (upstream, downstream and organizational processes). The findings indicate that the system-wide characteristic of resilience of the overall supply chain is not necessarily indicative of the resilience of its individual tiers.

High efficiency scores of a number of tiers forming a supply chain are shown to have only a limited effect on the overall efficiency score of the resulting supply chain. Overall, our research findings confirm the necessity of adopting both the system-wide and tier-specific approach by analysts and decision makers when assessing supply chain resilience. Integrated as part of risk response and mitigation process, the information obtained through such analytical approach ensures timely identification and mitigation of major sources of risk in the supply chains.

Supply chain resilience assessment models rarely consider resilience to risks at the level of individual supply chain tiers, focusing instead on the system-wide characteristics of supply chain resilience. The proposed analytical model allows for the assessment of supply chain resilience among individual tiers for a wide range of supply chain risks categorized as upstream, downstream, organizational, network and external.

The purpose of this systematic review is to evaluate the extant literature on depression and anxiety disorders in police using a multinational data set to determine whether the prevalence of these trauma-related disorders (TRMDs) is elevated in comparison to the general population.

Systematic review was employed in combination with best-evidence narrative synthesis to evaluate these hypotheses.

Despite wide variability in prevalence outcomes across the literature, strong evidence supports the hypothesis that the prevalence of depression is elevated in police, whereas moderate evidence supports the same hypothesis regarding anxiety. Preliminary evaluation of commonly examined predictive factors for each disorder demonstrated weak and inconsistent associations between these TRMDs and sociodemographic factors. No studies evaluated the relationship between incident-related factors (e.g. severity or frequency of exposure) and TRMDs, thus, at present, the literature on police is almost entirely unable to address the question of whether the prevalence of these disorders in police is influenced by exposure to work-related trauma.

The findings highlight a critical need for future work to address incident-related factors in predicting symptoms of depression and anxiety in police samples to determine whether these disorders bear a unique relationship to work-related traumatic exposure. Such work will significantly benefit the design and implementation of successful prevention and intervention strategies in the workplace.

The present review provides a comprehensive synthesis of a highly variable literature, highlighting critical gaps in our current knowledge of TRMDs in police and suggesting numerous avenues for future study.

Many studies have investigated how the structure of the collaborative networks of researchers influences the nature of their work, and its outcome. Co-authorship networks (CANs) have been widely looked at as proxies that can help bring understanding to the structure of research collaborative ties. The purpose of this paper is to provide a framework for describing what influences the formation of different research collaboration patterns.

The authors use social network analysis (SNA) to analyze the co-authorship ego networks of the ten most central authors in 24 years of papers (703 papers and 1,118 authors) published in the Proceedings of CASCON, a computer science conference. In order to understand what lead to the formation of the different CANs the authors examined, the authors conducted semi-structured interviews with these authors.

Based on this examination, the authors propose a typology that differentiates three styles of co-authorship: matchmaking, brokerage, and teamwork. The authors also provide quantitative SNA-based measures that can help place researchers’ CAN into one of these proposed categories. Given that many different network measures can describe the collaborative network structure of researchers, the authors believe it is important to identify specific network structures that would be meaningful when studying research collaboration. The proposed typology can offer guidance in choosing the appropriate measures for studying research collaboration.

The results presented in this paper highlight the value of combining SNA analysis with interviews when studying CAN. Moreover, the results show how co-authorship styles can be used to understand the mechanisms leading to the formation of collaborative ties among researchers. The authors discuss several potential implications of these findings for the study of research collaborations.