Indiana University East

ABSTRACT With nearly one-third of all workers in the United States now being remote, there is a need to use technology to meet organisational and personal goals. The potential of job crafting behaviours to influence technology acceptance in remote work settings has yet to be thoroughly investigated. Understanding how these behaviours affect technology perception can guide tailored interventions for diverse personality types. Anchored in the Job Characteristics Model and the Technology Acceptance Model, this study examines how job crafting behaviours influence perceptions of new technology among remote workers in the U.S. (N = 291). Our analysis reveals cognitive and relational crafting behaviours have varying impacts on the perceived ease of use and usefulness of technology. Cognitive crafting introduces complexities, reducing perceived effectiveness, while relational crafting enhances perceived usefulness. Task crafting positively impacts both ease of use and usefulness. These results underscore the importance of considering job crafting behaviours to enhance technology acceptance in remote work environments.

Based on social identity theory and the resilience literature, this study explored the ways social media impacted Asian Americans’ emotional well-being, racial identity negotiation, and coping strategies amid the surge in anti-Asian discourses during the Covid-19 pandemic. We interviewed 32 Asian Americans aged 18–59 ( M = 26.63, SD = 7.66; 28% = Ethnic Chinese) who had experienced anti-Asian sentiment on social media during the pandemic. Our study shows that social media played a contradictory role in how Asian Americans experience and cope with the surge in anti-Asian sentiment. Findings from our thematic analysis demonstrate that (1) the negative experiences of social media in conjunction with racial identity that influences Asian Americans’ psychological well-being, (2) the positive role of social media offering a space for collective solidarity, and (3) the positive role of social media activism as a means of collective coping and resilience.

Articles published in the academic journals of the Austrian School of economics are used to rank scholars and institutions by research productivity in Austrian economics over the 2011-2020 decade. The journals included in this survey are the Procesos de Mercado: Revista Europea de Economía Política, the Quarterly Journal of Austrian Economics, the Review of Austrian Economics, Cosmos + Taxis, Advances in Austrian Economics, and the Journal des Économistes et des Études Humaines. The methodology was developed to rank programs by mainstream research productivity in the social sciences but is adapted here to focus on exclusively Austrian School journals. The ranking exercise offers an opportunity to appraise and evaluate the Austrian School’s progress over the past decade. Implications for the future are suggested.

This paper investigates three distinct Monte Carlo estimators derived from the research of Sbert et al. These estimators are specifically tailored to the scattering equations using the Ward Bidirectional Reflectance Distribution Function (BRDF) integrated with a designed cosine-weighted environment map. In this paper, we have two goals. First, to bridge the gap between theoretical foundations and practical applicability to understand how these estimators can be seamlessly integrated as extensions to the acclaimed PBRT renderer. And the second is to measure their real-world performance. We aim to validate our methodology by comparing rendered images with varying convergence rates and deviations to the results of Sbert et al. This validation will ensure the robustness and reliability of our approaches. We analyze the analytical structure of these estimators to derive their precise form. We then implement the three estimators as extensions to the PBRT renderer, subjecting them to a numerical evaluation. We further evaluate the results of the estimator set and sampling strategy by utilizing another pair of incident radiance functions and BRDFs. The final step is to generate rendered images from the implementation to verify the results observed by Svart et el. and extend them with this new pair of functions.

PurposeThis paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.Design/methodology/approachAmong other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.FindingsStatistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.Originality/valueThe findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.

Suppose for n∈ ℕ, set A⊆ℝⁿ and function f∶A→ℝⁿ. If set A, using the Hausdorff outer measure, is measurable in the sense of Carathèodory; we want to find an extension of the expected value, w.r.t the Hausdorff measure, that's unique, finite and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. The issue is current extensions of the expected value are finite for all functions in only a shy subset of ℝᴬ. The reason this issue wasn't resolved is mathematicians have not thought of the problem, focusing on application rather than generalization. Despite the lack of potential use, we'll attempt to solve the problem by defining a choice function---this shall choose a unique set of equivalent sequences of sets (Fₖ***) , where the set-theoretic limit of Fₖ*** is the graph of f; the measure Hʰ is the ℎ-Hausdorff measure, such for each k∈ℕ, 0 < Hʰ(Fₖ***) < +∞; and (fₖ*) is a sequence of functions where {(x,fₖ*(x))∶x∈ dom(Fₖ***)}=Fₖ***. Thus, the extended expected value of or E**[f,Fₖ***] is: ∀(ε>0)∃(N∈ℕ)∀(k∈N)(k≥N⇒1/Hʰ(dom(Fₖ***))∫dom(Fₖ*** )fₖ* dHʰ - E**[f,Fₖ***]<ε ) which should be unique, finite, and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. Note we guessed the choice function using computer programming but we don’t use mathematical proofs due to the lack of expertise in the subject matter. Despite this, the biggest use of this research is the extension of the expected value is finite for "almost all" functions: this is easier to use in application when finding the "average" of functions covering an infinite expanse of space.

Suppose for n∈ ℕ, set A⊆ℝⁿ and function f∶A→ ℝⁿ. If set A, using the Hausdorff outer measure, is measurable in the sense of Carathèodory; we want to find an extension of the expected value, w.r.t the Hausdorff measure, that's unique, finite and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. The issue is current extensions of the expected value are finite for all functions in only a shy subset of ℝᴬ. The reason this issue wasn't resolved is mathematicians have not thought of the problem, focusing on application rather than generalization. Despite the lack of potential use, we'll attempt to solve the problem by defining a choice function---this shall choose a unique set of equivalent sequences of sets (Fₖ***) , where the set-theoretic limit of Fₖ*** is the graph of f; the measure Hʰ is the ℎ-Hausdorff measure, such for each k∈ℕ, 0 < Hʰ(Fₖ***) < +∞; and (fₖ*) is a sequence of functions where {(x,fₖ*(x))∶x∈ dom(Fₖ***)}=Fₖ***. Thus, the extended expected value of or E**[f,Fₖ***] is: ∀(ε>0)∃(N∈ℕ)∀(k∈N)(k≥N⇒1/Hʰ(dom(Fₖ***))∫dom(Fₖ*** )fₖ* dHʰ - E**[f,Fₖ***]<ε ) which should be unique, finite, and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. Note we guessed the choice function using computer programming but we don’t use mathematical proofs due to the lack of expertise in the subject matter. Despite this, the biggest use of this research is the extension of the expected value is finite for "almost all" functions: this is easier to use in application when finding the "average" of functions covering an infinite expanse of space.