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Even though trust is known for improving supply chain performance (SCP), previous studies have overlooked the investigation of its dimensions. Limited studies exist on the variations of the influence of trust dimensions in agribusiness supply chain relationships. This study examined the influence of trust dimensions on SCP in a developing country's context.

A cross-sectional study design was used to collect from 204 farmers and 192 traders (396 respondents) using a multistage sampling approach. Structural equation modeling was employed to analyze the hypothesized relationships.

Pooled sample results show that integrity and competence were the trust dimensions with significant effects on SCP, whereas competence was significant across different supply chains and markets, integrity and benevolence were only significant along fresh chains and in the contract market.

The extent of application of this study's findings is limited to situations similar to those of tomato and soybeans value chains in developing countries.

The paper contributes to a better understanding of the influence of trust dimensions on SCP across supply chains in different market typologies in agribusiness relationships in a developing country's context.

I am concerned with insights heterodox economics, and particularly the new institution economics, can offer regarding interactions between health emergencies and the airline industry. Air services not only facilitates the transmissions of diseases among humans, and between animals, but on the positive side, can expedite the movement of medicines and the transfer of those afflicted during pandemics and epidemics. They can serve to limit the outbreak of disease by providing “mercy flights” to regions poorly served by other modes. Significant challenge confronting carriers during a major event, however, often included immediate financial shocks as well as ensuring their operations do not contribute to the spread of disease. These economic challenges for both commercial carriers and public policymakers involve sources of finance for what is, in this context, a semi-public service as well as the extent to which airlines should retain standby capacity extending resilience to the air-service supply chain. Conventional neoclassical economics, while still at the center of analyzing many of these sorts of issues, has increasingly, because of its rigid assumption and poor forecasting record, been supplemented by heterodox economic thinking. This trend has been reinforced by progress in fields such as psychology. What I demonstrate is that heterodox economics, and especially the role of institutions, offers a more complete picture of the interactions between air transportation and the spread of disease.

The purpose of this paper is to advocate for the integration of quantitative reasoning into management education and leadership development literature. The authors argue that the increasing complexity of managerial decision contexts, particularly in the age of information overload, demands that leaders possess the ability to critically analyze and interpret quantitative information.

This viewpoint paper uses narrative argument to explore the concept of quantitative reasoning and its relevance to management education. The authors draw on research from mathematics education, psychology and management to support their argument. They also use real-world examples, such as the COVID-19 pandemic, to illustrate the importance of quantitative reasoning in contemporary leadership.

This paper argues that quantitative reasoning is a critical skill for organizational leaders. It highlights the limitations of traditional management education in preparing leaders to effectively navigate data-rich environments. The authors contend that incorporating quantitative reasoning into leadership development programs can improve decision-making effectiveness.

This paper offers a novel perspective on leadership development by emphasizing the significance of quantitative reasoning, a concept borrowed from the field of mathematics education, to close a gap in current management education practices.

Knowledge of how social movements move, diffuse, and expand collective action events is central to movement scholarship and activist practice. Our purpose is to extend sociological knowledge about how movements (sometimes) diffuse and amplify insurgent actions, that is, how movements move. We extend movement diffusion theory by drawing a conceptual analogue with military theory and practice applied to the case of the organized and highly disciplined nonviolent Nashville civil rights movement in the late 1950s and early 1960s. We emphasize emplacement in a base-mission extension model whereby a movement base is built in a community establishing a social movement school for inculcating discipline and performative training in cadre who engage in insurgent operations extended from that base to outlying events and campaigns. Our data are drawn from secondary sources and semi-structured interviews conducted with participants of the Nashville civil rights movement. The analytic strategy employs a variant of the “extended case method,” where extension is constituted by movement agents following paths from base to outlying campaigns or events. Evidence shows that the Nashville movement established an exemplary local movement base that led to important changes in that city but also spawned traveling movement cadre who moved movement actions in an extensive series of pathways linking the Nashville base to events and campaigns across the southern theater of the civil rights movement. We conclude with theoretical and practical implications.

Throughout the 21st century, US households have experienced unprecedented levels of leverage. This dynamic has been exacerbated by income shortfalls during the COVID-19 crisis. Leveraging and deleveraging decisions affect household consumption. This study investigates the effect of the dynamics of household leverage and consumption on the stock market.

The authors explore the relation between household leverage and consumption in the context of the consumption capital asset pricing model (CCAPM). The authors test the model's implication that leverage has a negative risk premium by transforming the asset pricing restriction into an unconditional linear factor model and estimate the model using the general method of moments procedure. The authors run time-series regressions to estimate individual stocks' exposures to leverage, and cross-sectional regressions to investigate the leverage risk premium.

The authors show that shocks to household debt have strong and lasting effects on consumption growth. The authors extend the CCAPM to accommodate this effect and find, using various test assets, a negative risk premium associated with household deleveraging. Looking at individual stocks the authors show that the deleveraging risk premium is not explained by well-known risk factors.

This paper contributes to the literature on the role of leverage in economics and finance by establishing a relation between household leverage and spending decisions. The authors provide novel evidence that households' leveraging and deleveraging decisions can be a fundamental and influential force in determining asset prices. Further, this paper argues that household leverage might explain the small, persistent, and predictable component in consumption growth hypothesised in the long-run risk asset pricing literature.

The concept of ‘intelligence’ used to differ between human and machines, until the disruption of artificial intelligence (AI). The field of AI is advancing far more rapidly than the establishment of rules and regulations, which is causing certain fear. However, slowing down this progression to avoid economic crisis is not an option because of open-source AI, which facilitates faster development processes and collective contributions to codes and algorithms. Public policies, such as the ‘European Union AI Act (EU AI)’, ‘Whitehouse AI’, and the G7's ‘Hiroshima Artificial Intelligence Process’ (HAP), are already drafted. Regulators need to adopt a dynamic approach given AI's rapid advancement, and they need to eventually strive for international harmonisation in their rules and regulations for better collaborations. The EU's AI Act is the ‘world's first comprehensive law’ and it focuses on five main pillars similar to other countries drafts: ensuring AI usage is safe, transparent, traceable, non-discriminatory and environmentally friendly. They portray four risk categories against which citizens can file complaints: (1) Unacceptable risk (2) High risk (3) Generative AI (4) Limited risk. The US AI policies include ‘The Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People’ and the ‘Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence’. This conceptual study extensively reviews the concept of AI and compares pioneering draft laws while providing recommendations on ethics and responsible AI. The contribution of this study is that it sheds light on the evolving evolution of AI and the challenges posed by the rapid advancement of AI technology, emphasising the necessity for flexible and adaptive regulatory frameworks. This is the first paper to explore AI from the academic and political perspective.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

The ageing and disabled population is fast growing, which emphasises the need to effectively modify current homes and environments to support healthy ageing and increasingly diverse health needs. This paper aims to bring together findings and analyses from three adaptations-focussed projects, drawing on perspectives from key stakeholders alongside the lived experiences of service users acquiring adaptations.

Following an Adaptations Framework developed from interviews and focus groups with older people and key stakeholders, the paper discusses barriers experienced by older people and front-line workers in receiving and delivering adaptations through all stages of the process.

This paper reveals how experiences around adaptations might diverge with unseen, hidden investment and need amongst individuals, and how conceptual and cost-focussed evidence gaps impact wider understandings of adaptations delivery. In so doing, this paper highlights how the adaptations process is perceived as a “fight” that does not work smoothly for either those delivering or receiving adaptations services.

The paper suggests a systematic failure such that the adaptations process needs to be rehauled, reset and prioritised within social and public policy if the housing, health and social care sectors are to support healthy ageing and prepare for the future ageing population.

The paper brings together insights from key stakeholders alongside service users' experiences of adaptations to highlight key policy drivers and barriers to accessing and delivering adaptations.

This paper aims to provide a novel explorative perspective on fund managers’ decisions under uncertainty. The current COVID pandemic is used as a unique reference frame to study how heuristics are used in institutional financial practice.

This study follows a grounded theory approach. A total of 282 diverse publications between October 2019 and October 2020 for 20 German mutual funds are qualitatively analyzed. A theory of adaptive heuristics for fund managers is developed.

Fund managers adapt their heuristics during a crisis and this adaptive process flows through three stages. Increasing complexity in the environment leads to the adaption of simplest heuristics around investment decisions. Three distinct stages of adaption: precrisis, uncertainty and stabilization emerge from the data.

This study’s data is based on publicly available information. There might be a discrepancy between publicly stated and internal reasoning.

Money managers can use the provided framework to assess their decision-making in crises. The developed adaptive processes of heuristics can assist capital allocators who choose and rate fund managers. Policymakers and regulators can learn about the aspects of investor decisions that their actions and communication address. Teaching can use this study to exemplify the nature of financial markets as adaptive systems rather than static structures.

To the best of the author’s/authors’ knowledge, this study is the first to systematically explore the heuristics of professional money managers because they navigate a large-scale exogenous crisis.