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This research explores how contextual elements and significant events influence the changing storylines within a company's directors' reports spanning a period of six decades. These elements and events encompass the internal dynamics of the family that owns the company, industry-specific advancements, political and socioeconomic climates, and explicit guidelines related to corporate reporting.

This research employs a case study methodology to analyse the directors' reports of Barilla, a prominent Italian food manufacturer, within the theoretical framework of historical institutionalism. A systematic content analysis is conducted on sixty directors' reports published between 1961 and 2021. The study also identifies and examines significant contextual events within this six-decade period, which are linked to four key institutional factors.

Based on the research findings, the directors' reports exhibited notable fluctuations throughout the studied timeframe in reaction to shifts in the institutional setting. Our investigation highlights that each institutional element experienced crucial pivotal moments, and given their interconnected nature, modifications in one factor impacted the others. It was noted that these pivotal moments resulted in alterations in the directors' reports' content across various thematic areas. Additionally, despite Barilla being a multinational company, it was found that national events within Italy had a more pronounced influence on the evolving narratives than global events.

Previous research on directors' reports or chairman's statements has primarily focused on the influence of macro-level institutional factors on the narratives. In contrast, our study considers both macro-level and micro-level institutions, specifically examining the internal events within a family business and how they shape the content of directors' reports. Our study is also distinctive in its analysis of specific critical junctures and their interactions with the investigated institutional factors. Additionally, to the best of our knowledge, few existing studies span a timeframe of sixty years, particularly concerning an Italian company.

The purpose of this study is to ascertain how foreign and domestic Exchange Traded Funds (ETFs) investing in Indian equities affect their return volatility and pricing efficiency. Further, we investigate how the difference in market timings affect the impact of ETFs on their constituents. Lastly, we examine how these effects vary during tranquil and turmoil periods in the ETF markets.

The study is based on quarterly data for stocks comprising the CNX Nifty 50 Index from 2009Q1 to 2019Q3. The data on holdings of 45 domestic and 196 foreign ETFs in the sample stocks were obtained from Thomson Reuters' Eikon. The paper employs a panel-regression methodology with stock and time fixed effects and robust standard errors.

Foreign ETFs from North America and the Asia Pacific largely have an adverse impact on stocks' return volatility. In times of turmoil, stocks with higher coverage of European, North American and Domestic funds are susceptible to volatility shocks emanating from these regions. European and Asia Pacific ETFs are associated with improved price discovery while North American funds impound a mean-reverting component in stock prices. However, in turbulent markets, both positive and negative impacts of ETFs on pricing efficiency coexist.

To the best of the authors' knowledge, this is the first study that examines the impact of domestic as well as foreign ETFs on the equities of an emerging market. Furthermore, the study is unique as we investigate how the effects of ETFs vary in turbulent and tranquil markets. Moreover, the paper examines the role of asynchronous market timings in determining the ETF impact. The paper adds to the growing literature on the unintended consequences of index-linked products.

This study’s purpose is to analyze the effects of trade interventions and non-tariff impediments between the exporters (the United States and Brazil) and China for soybean trade.

A spatial model is developed and solved using an optimized Monte Carlo simulation (OMCS) and is used to minimize the costs of supplying soybeans to China. The costs included the origin basis; transportation to ports, including trucks, railways and barges; demurrage; and ocean freight. The sum of these charges determines the delivered costs to China from each origin. Most variables are random and correlated. Time-series distributions are based on historical data. Production and exports are highly seasonal and important.

Base-case flows are highly seasonal, are risky and reflect actual trade. Sensitivities illustrate the effects of mitigating the quality differentials and interpreting a term of the Phase One agreement that purchases would be made so long as the prices are competitive. The results are also used to illustrate the influence of diversifying from the United States as a supplier. Finally, the policy implications are discussed.

Removing the quality discounts for US soybeans raises the US market share by 9%. These results also illustrate that diversification of supply sources is important for the importing country. Indeed, if China were to pursue less diversification import costs and/or risks would escalate. Hence, these results suggest that diversification is an appealing element of an import strategy. The results suggest a large distribution of prices and costs, particularly in Brazil. On average, the United States is most likely to be competitive for only a few months of the year, and the results are highly seasonal.

Competition in supplying soybean to China is extremely competitive and the underlying factors impacting spatial competition are risk, correlated and spatially dependent. In addition to these, there are quality differences, and there are trade policies and strategies that affect competition. The empirical model and results illustrate the intensity of competition in this market as well the impacts of these non-tariff barriers and trade strategies in this market.

Important policies have been taken and continue to be under review regarding competition and trade among these countries. These results illustrate the impacts of these policies on market shares and competition.

This problem is important to the world soybean trading sector, and the methodology captures important seasonal and random variables that affect trade flows. The OMCS model is appropriate for this problem and has only been used minimally in the recent literature about commodity trade.

Internationalisation and academic mobility have long been integral parts, although serving different purposes in the higher education industry. Internationalisation has played a crucial role in facilitating academic exchange, knowledge sharing, research partnerships and collaborative innovation. However, the rise of neoliberalism has introduced the market forces of global capitalism that have significantly impacted higher education worldwide – invading the sector with neoliberal market values. This chapter aims to explore the impact of neoliberalism on the internationalisation of higher education in Africa, with a specific focus on trends in international student mobility. The chapter argues that the influence of neoliberalism on international mobility extends beyond market dynamics, encompassing discussions on hegemony within international knowledge systems, where African countries and institutions often find themselves marginalised. The study relies on published materials and publicly available statistical data from both governmental and non-governmental organisations. By examining the interplay between neoliberalism and the process of internationalisation in higher education, this chapter sheds light on the intricate and multifaceted aspects of both concepts, as well as their practical implications for international student mobility. Moreover, the chapter reflects on the implications of neoliberal entanglements for the prospects of internationalisation in African higher education.

Understanding when an individual is being deceptive is an important part of police and criminal investigations. While investigators have developed multiple methods, the research literature has yet to fully explore some of the newer applied techniques. This study aims to investigate statement analysis, a recent approach in forensic linguistic analysis that has been applied to criminal investigations.

Real-world statements of individuals exposed as deceptive or truthful were used in the analyses. A behaviour sequence analysis approach is used to provide a timeline analysis of the individuals’ statements.

Results indicate that sequential patterns are different in deceptive statements compared to truthful statements. For example, deceptive statements were more likely to include vague words and temporal lacunas, to convince investigators into believing that the suspect was not present when the crime occurred. The sample in this research did not use one deceptive indicator, instead, electing to frequently change the order of deceptive indicators. Gaps in deception were also noted, and there was common repetition found in both the deceptive and truthful statements. While gaps are predicted to occur in truthful statements to reflect an absence of deception, gaps occurring in the deceptive statements are likely due to cognitive load.

The current research provides more support for using statement analysis in real-world criminal cases.

The purpose of this paper is to address the complexity of missing persons cases and highlight the linguistic differences that arise in this type of crime. Missing persons cases are typically very complex investigations. Without a body, crime scene forensics is not possible, and police are often left only with witness and suspect statements. Forensic linguistics methods may help investigators to prioritise or remove suspects. There are many competing approaches in forensic linguistic analysis; however, there is limited empirical research available on emerging methods.

This research investigates Statement Analysis, a recent development in linguistic analysis that has practical applications in criminal investigations. Real-world statements of individuals convicted of or found to be not guilty of their involvement in missing persons cases were used in the analyses. In addition, Behaviour Sequence Analysis was used to map the progressions of language in the suspects' statements.

Results indicated differences between the guilty and innocent individuals based on their language choices, for example, guilty suspects in missing [alive] cases were found more likely to use passive language and vague words because of high levels of cognitive load associated with the several types of guilty knowledge suspects in missing persons cases possess. Of particular interest is the use of untruthful words in the innocent suspects’ statements in missing [murdered] cases. While typically seen in deceptive statements, untruthful words in innocent statements may result because of false acquittals.

This research provides some support for Statement Analysis as a suitable approach to analysing linguistic statements in missing persons cases.