The Nelson–Siegel model is widely used in fixed income markets to produce yield curve dynamics. The multiple time-dependent parameter model conveniently addresses the level, slope, and curvature dynamics of the yield curves. In this study, we present a novel state-space functional regression model that incorporates a dynamic Nelson–Siegel (DNS) model and functional regression formulations applied to a multi-economy setting. This framework offers distinct advantages in explaining the relative spreads in yields between a reference economy and a response economy. To address the inherent challenges of model calibration, a kernel principal component analysis is employed to transform the representation of functional regression into a finite-dimensional, tractable estimation problem. A comprehensive empirical analysis is conducted to assess the efficacy of the functional regression approach, including an in-sample performance comparison with the DNS model. We conducted the stress testing analysis of the yield curves’ term structure within a dual economy framework. The bond ladder portfolio was examined through a case study focused on spread modeling using historical data for US Treasury and UK bonds.

This article analyses the integration of Southern Italy into the first wave of financial globalization through the lens of transnational business groups (BGs) and relational infrastructures. Drawing on an original micro-level dataset and employing advanced Social Network Analysis (SNA) techniques, we map the evolving structure of business and financial relationships that connected the Neapolitan periphery to core European financial centres in the nineteenth century.

The article offers a relational reinterpretation of peripheral integration, showing that global capitalism advanced not merely through markets or states, but through densely structured networks of trust, influence and institutional proximity. It proposes a methodological and conceptual framework relevant to comparative histories of financial globalization and to rethinking the role of peripheries in shaping, and not just receiving, the trajectories of modern capitalism.

In spite of the omnibus property of integrated conditional moment (ICM) specification tests, they are not commonly used in empirical practice owing to features such as the non-pivotality of the test and the high computational cost of available bootstrap schemes, especially in large samples. This article proposes specification and mean independence tests based on ICM metrics. The proposed test exhibits consistency, asymptotic $\chi ^2$-distribution under the null hypothesis, and computational efficiency. Moreover, it demonstrates robustness to heteroskedasticity of unknown form and can be adapted to enhance power toward specific alternatives. A power comparison with classical bootstrap-based ICM tests using Bahadur slopes is also provided. Monte Carlo simulations are conducted to showcase the excellent size control and competitive power of the proposed test.

Transitioning to a sustainable economy requires firms to transform their business models in accordance with circular economy principles. Circular economy scholarship has predominantly examined resource-rich large firms and circular startups, leaving established, resource-constrained small-to-medium-sized enterprises (SMEs) underexplored. Facing capability constraints regarding resources, knowledge, and organizational capacity, government policy intervention plays an important role. Through interviews with 15 experts and analysis of seven government programs, we reveal the transition dynamics that shape SME circular engagement and how government intervention can reinforce the optimization of linear business models or facilitate moving toward circular business model transformation.

Understanding the values held by negotiating parties is central to the design and success of international climate change agreements. However, empirical understandings of these values – and the manners by which they structure negotiating countries’ value networks and interactions over time – are severely limited. In addressing this shortcoming, this paper uses keyword-assisted topic models to extract value networks for the 13 most recent Conferences of the Parties (COPs) to the United Nations Framework Convention on Climate Change (UNFCCC). It then uses network analysis tools to unpack these networks in relation to influential values, countries, and time. In doing so, it demonstrates that countries’ core climate change values (i) can be accurately recovered from COP High-level Segment (HLS) speeches and (ii) can, in turn, be used to understand the structure of negotiation networks at the UNFCCC. Analysis of the corresponding value networks for COPs 16–28 indicates that initially central values of “Fairness” and “Power” have increasingly given way to values associated with the “Environment” and “Achievement.” Thus, countries at the UNFCCC have increasingly eschewed values associated with common but differentiated responsibilities in favor of a consensus over the urgency of collectively combating climate change. These and related insights illustrate our approach’s potential for recovering and understanding value networks within climate change negotiations – a critical first step for any successful climate change agreement.

The rapid expansion of artificial intelligence has accelerated its adoption across organizational functions. However, existing reviews often adopt sectoral or technology-focused perspectives, limiting understanding of its implementation within core firm activities. This study addresses this gap through a systematic review of articles published in Web of Science and Scopus up to December 2025, following established methodological guidelines. A total of 160 peer-reviewed articles met the inclusion criteria. Findings reveal convergent patterns of adoption in human resources, marketing and customer services, logistics, and finance. Artificial intelligence enhances analytics, automates routine tasks, personalizes interactions, and supports decision-making. Human resources applications focus on recruitment and workforce planning; marketing relies on predictive analytics and conversational interfaces; logistics improves forecasting and supply chain resilience; finance strengthens risk assessment and process efficiency. The study proposes an integrative conceptual model and research propositions, highlighting cross-functional challenges in governance, organizational capabilities, socio-technical alignment, and responsible implementation.

The Covid-19 pandemic has negatively affected labour markets, among other aspects of life. This study examines the impact of the discouraged worker effect during the pandemic, focusing on the Turkish labour market from 2018 to 2021. Although few studies exist on this topic, they rely on labour force participation rates, whereas our dataset includes direct questions and data specifically related to the discouraged worker effect, allowing for a microeconomic analysis. Probit regression results show that the discouraged worker effect was stronger during the pandemic, with job seekers being 1.6% more likely to become discouraged than before. Higher education levels generally reduce this likelihood, both before and during the pandemic. While age negatively correlates with discouragement, this effect diminishes with increasing age. Single women were more adversely affected than single men and married women than married men. Higher unemployment rates increase discouragement, as expected, while an increase in the unemployment rate has a greater effect on individuals during the pandemic period. Findings suggest that the pandemic had a disproportionate impact on certain individuals, particularly with respect to education level and gender, while Türkiye’s societal structure may help explain the observed gender-based differences.

Affective Events Theory explains how workplace emotions arise from discrete events and shape attitudes and behaviour. Drawing on a phenomenological study of 29 employees and 13 managers working within oversight saturated supervisory contexts in the post–Royal Commission Australian financial services sector, this paper extends Affective Events Theory by examining how affective experience unfolds when accountability is continuous, and discretion is constrained. Across dual-cohort findings, affect was not primarily anchored to identifiable events that resolved over time. Instead, participants described emotion as persistent and cumulative, produced through ambiguity and emotional restraint, and circulating across supervisory roles. Employees reported sustained interpretive effort directed towards reading tone, silence, and procedural communication, while managers described regulating emotional expression to remain defensible under accountability pressures. These findings specify boundary conditions for the episodic logic of Affective Events Theory, by explaining how affect may be conceived as a sustained condition in contexts with sustained oversight, with meaningful implications for workplace attitudes and behaviours and for managerial practice in highly regulated organisational environments where accountability and supervision are continuous.

Drawing on Joseph Carens’s social membership theory, originally developed in immigration ethics, I transpose this temporal logic to organizational spheres. I argue that as employees accrue tenure, they “sink roots”, integrating into the firm’s cooperative structure and subjecting themselves to its governance. This sustained integration generates increasingly strong moral entitlements to participate in decision-making, analogous to how long-term residents acquire claims to citizenship. I use this temporal framework to address the boundary problem in workplace democracy, defend a graduated workplace franchise that prioritizes long-term employees over transient stakeholders, and criticize fissured employment structures that block such membership over time.

Many theorists tie social norms to attitudes, such as expectations towards others, perhaps along with conforming practices. Challenging this view, we instead ground social norms in a social norming process, an often non-verbal social communication process that ‘makes’ the norm through mutual expressions of support. We present the process-based account of social norms and social normativity, and distinguish social norms from social pressures, social practices and Lewisian conventions. The process-based view brings social norms closer to legal norms, by tying them to ‘expressive acts’, just as laws and contracts arise through acts of voting or signing, not through mere attitudes.