Empirical Test Research Articles

Unravelling the Interplay of Servant Leadership, Cognitive Trust, and Employee Wellbeing: A Cae of An Emerging Economy

This study examines the relationship between servant leadership, cognitive-based trust, and employee wellbeing in Pakistan's healthcare sector. Grounded in existing research, our study explains the theoretical underpinnings of servant leadership, cognitive-based trust, and employee wellbeing. Servant leadership prioritizes followers' needs, fostering positive outcomes such as organizational citizenship behavior and job engagement. Cognitive-based trust, rooted in transparent communication and shared values, is fundamental to healthy leader-follower relationships and organizational commitment. Employee wellbeing, encompassing physical and psychological dimensions, is crucial for organizational success. In Pakistan's healthcare sector, marked by its complexity and the need for positive work environments, this study investigates how servant leadership and cognitive-based trust impact employee wellbeing. Four hypotheses are formulated: (1) Servant leadership positively correlates with overall employee wellbeing, (2) Servant leadership positively influences cognitive-based trust development, (3) Higher levels of cognitive-based trust correlate with enhanced wellbeing, and (4) Servant leadership's positive influence on wellbeing is mediated by cognitive-based trust. Through empirical testing, this research aims to deepen understanding of leadership, trust, and wellbeing dynamics in healthcare, providing insights for organizational practices. By elucidating these relationships, the study seeks to contribute to the creation of flourishing and sustainable workplaces in Pakistan's healthcare sector.

Research on the Impact of Trade Policy Uncertainty on the Digital Transformation of Chinese Export Firms

Abstract This paper uses data from listed companies in China from 2007 to 2022 to prove that the increase in trade policy uncertainty has promoted the digital transformation process of Chinese export firms. Through theoretical analysis and empirical testing, we found that the promotion effect of trade policy uncertainty on the digital transformation of Chinese export firms is related to trade costs. Rising trade policy uncertainty has increased trade costs, which in turn has forced Chinese exporters to accelerate their digital transformation. Digital capabilities are used to resolve cost challenges brought about by trade policy uncertainty. In addition, this paper also finds that when trade policy uncertainty promotes the digital transformation of Chinese exporters, foreign investment will significantly strengthen this role, while financing constraints will weaken this role, reflecting the importance of foreign investment. Finally, we found that the increase in trade policy uncertainty reduces the imbalance of digital development levels in industries and regions, promotes the digital transformation of industries and regions with lower digitalization levels, and is conducive to promoting the balanced development of digitalization in industries and regions in a country. Keywords: trade policy uncertainty, digital transformation, Chinese export firms.

The Pathways of Digital Innovation in Manufacturing Enterprises: Based on Dynamic Capabilitie

As the global digital economy continues to evolve, manufacturing companies are encountering the necessity to shift from conventional methods to digital solutions, including cloud services and big data analytics. The objective of this research is to investigate the ways in which the capabilities of digital platforms facilitate digital innovation within enterprises. Grounded in the relevant theories of dynamic capability and open innovation, a research model among variables is constructed, and empirical test is conducted through a questionnaire. The findings of the analysis indicate that: First, digital platform capability promotes the realization of digital innovation through the joint action of platform integration and platform reconstruction; Second, organizational agility plays a partially mediating role. The research results have some practical guiding value for manufacturing enterprises to realize innovation by using information technology during the digital economic era.

The time course of encoding specific and gist episodic memory representations among young and older adults.

How rapidly can we encode the specifics versus the gist of episodic memories? Competing theories have opposing answers, but empirical tests are based primarily on tasks of item memory. Few studies have addressed this question with tasks measuring the binding of event components (e.g., a person and a location), which forms the core of episodic memory. None of these prior studies included older adults, whose episodic memories are less specific in nature. We addressed this critical gap by presenting face-scene pairs (e.g., an old man with a park) at various encoding presentation rates to 80 young (M = 21.83 years) and 86 older (M = 68.62 years) adults. Participants completed associative recognition tests featuring old/intact (e.g., the old man with the same park), similar (e.g., the old man with a different park), and unrelated (e.g., the old man with a kitchen) pairs. Multinomial-processing-tree model analyses revealed that young and older adults encoded each pair's gist representation more rapidly than its specific representation, supporting fuzzy-trace theory. No age-related differences in gist representations were obtained at any presentation rate, but older adults required more time to encode specific representations commensurate with those of younger adults. However, older adults' abilities to retrieve these representations were cue-dependent, as they were more susceptible than younger adults to experiencing vivid false memories of similar lures. These phantom recollections were remediated with further increases in encoding time. Thus, slower speed of encoding partially underlies age-related declines in episodic memory specificity, but retrieval mechanisms also play a role. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cortical parenchyma wall width regulates root metabolic cost and maize performance under suboptimal water availability.

We describe how increased root cortical parenchyma wall width (CPW) can improve tolerance to drought stress in maize by reducing the metabolic costs of soil exploration. Significant variation (1.0 to 5.0 µm) for CPW was observed in maize germplasm. The functional-structural model RootSlice predicts that increasing CPW from 2 to 4 µm is associated with ca. 15% reduction in root cortical cytoplasmic volume, respiration rate, and nitrogen content. Analysis of genotypes with contrasting CPW grown with and without water stress in the field confirms that increased CPW is correlated with ca. 32 to 42% decrease in root respiration. Under water stress in the field, increased CPW is correlated with 125% increased stomatal conductance, 325% increased leaf CO2 assimilation rate, 73 to 78% increased shoot biomass, and 92 to 108% increased yield. CPW was correlated with leaf mesophyll midrib parenchyma wall width, indicating pleiotropy. GWAS analysis identified candidate genes underlying CPW. OpenSimRoot modeling predicts that a reduction in root respiration due to increased CPW would also benefit maize growth under suboptimal nitrogen, which requires empirical testing. We propose CPW as a new phene that has utility under edaphic stress meriting further investigation.

Gain and loss cycles revisited: What to consider when testing key assumptions of conservation of resources theory

In this editorial, we discuss approaches to the empirical test of gain and loss cycles as described within Hobfoll's conservation of resources theory (COR). We present COR theory's basic assumptions about gain and loss cycles and critically discuss typical empirical studies that aim at testing these assumptions. We highlight conceptual and empirical problems when testing gain and loss cycles of resources and provide guidance for researchers with respect to theoretical, temporal, and data-analytic aspects. We offer some suggestions for constructive replications and reproducibility.

Long-Term Taste and Smell Outcomes After COVID-19

Self-report surveys suggest that long-lasting taste deficits may occur after SARS-CoV-2 infection, influencing nutrition, safety, and quality of life. However, self-reports of taste dysfunction are inaccurate, commonly reflecting deficits due to olfactory not taste system pathology; hence, quantitative testing is needed to verify the association of post-COVID-19 condition with taste function. To use well-validated self-administered psychophysical tests to investigate the association of COVID-19 with long-term outcomes in taste and smell function. This nationwide cross-sectional study included individuals with and without a prior history of COVID-19 recruited from February 2020 to August 2023 from a social media website (Reddit) and bulletin board advertisements. In the COVID-19 cohort, there was a mean of 395 days (95% CI, 363-425 days) between diagnosis and testing. History of COVID-19. The 53-item Waterless Empirical Taste Test (WETT) and 40-item University of Pennsylvania Smell Identification Test (UPSIT) were used to assess taste and smell function. Total WETT and UPSIT scores and WETT subtest scores of sucrose, citric acid, sodium chloride, caffeine, and monosodium glutamate were assessed for groups with and without a COVID-19 history. The association of COVID-19 with taste and smell outcomes was assessed using analysis of covariance, χ2, and Fisher exact probability tests. Tests were completed by 340 individuals with prior COVID-19 (128 males [37.6%] and 212 females [62.4%]; mean [SD] age, 39.04 [14.35] years) and 434 individuals with no such history (154 males [35.5%] and 280 females [64.5%]; mean (SD) age, 39.99 [15.61] years). Taste scores did not differ between individuals with and without previous COVID-19 (total WETT age- and sex-adjusted mean score, 33.41 [95% CI, 32.37-34.45] vs 33.46 [95% CI, 32.54-34.38]; P = .94). In contrast, UPSIT scores were lower in the group with previous COVID-19 than the group without previous COVID-19 (mean score, 34.39 [95% CI, 33.86-34.92] vs 35.86 [95% CI, 35.39-36.33]; P < .001]); 103 individuals with prior COVID-19 (30.3%) and 91 individuals without prior COVID-19 (21.0%) had some degree of dysfunction (odds ratio, 1.64 [95% CI, 1.18-2.27]). The SARS-CoV-2 variant present at the time of infection was associated with smell outcomes; individuals with original untyped and Alpha variant infections exhibited more loss than those with other variant infections; for example, total to severe loss occurred in 10 of 42 individuals with Alpha variant infections (23.8%) and 7 of 52 individuals with original variant infections (13.5%) compared with 12 of 434 individuals with no COVID-19 history (2.8%) (P < .001 for all). In this study, taste dysfunction as measured objectively was absent 1 year after exposure to COVID-19 while some smell loss remained in nearly one-third of individuals with this exposure, likely explaining taste complaints of many individuals with post-COVID-19 condition. Infection with earlier untyped and Alpha variants was associated with the greatest degree of smell loss.

Causality between Greenfield Investments, Regulatory Quality, and Economic growth: Is the Western Balkans different?

The study aims to examine the causality link between Greenfield Investments, Regulatory Quality, and Economic Growth by using seven Western Balkan countries between 2003 and 2022. Johansen cointegration tests, the VECM model, and multiple empirical unit root tests are the foundation of the empirical analysis. The study's findings indicate that, in the short run, GFI-led growth in Albania and North Macedonia is supported. In the long run, the analysis backs the growth driven by GFI in Serbia and Montenegro and the growth driven by regulatory quality in Albania, Bosnia and Herzegovina, North Macedonia, Serbia, Montenegro, and Bulgaria. The findings support the growth driven by regulatory quality in most Western Balkan countries, reassuring national policymakers that encouraging improvements in regulatory quality and GFI inflows is warranted and will ultimately spur economic growth.

Hydrogels and Carbon Nanotubes: Composite Electrode Materials for Long-Term Electrocardiography Monitoring

This paper presents methods for developing high-performance interface electrode materials designed to enhance signal collection efficacy during long-term (over 24 h) electrocardiography (ECG) monitoring. The electrode materials are fabricated by integrating commercial ECG liquid hydrogels with carbon nanotubes (CNTs), which are widely utilized in dry-electrode technologies and extensively discussed in the current scientific literature. The composite materials are either prepared by dispersing CNTs within the commercial liquid hydrogel matrix or by encasing the hydrogels in macroscopic CNT films. Both approaches ensure the optimal wetting of the epidermis via the hydrogels, while the CNTs reduce material impedance and stabilize the drying process. The resulting electrode materials maintain their softness, allowing for micro-conformal skin attachment, and are biocompatible. Empirical testing confirms that the ECG electrodes employing these hybrid hydrogels adhere to relevant standards for durations exceeding 24 h. These innovative hybrid solutions merge the benefits of both wet and dry ECG electrode technologies, potentially facilitating the extended monitoring of ECG signals and thus advancing the diagnosis and treatment of various cardiac conditions.

EXPRESS: Magnify Cascades of eWOM on Social Networks: the Roles of User, Product, and Relationship Characteristics

Firms are increasingly relying on electronic word-of-mouth (eWOM), in the form of online reviews and social media posts, to sell their products or services. A pivotal component of managing eWOM is to understand and, potentially influence, how one consumer’s eWOM can lead to another’s – a process called behavioral cascading. While prior eWOM research has established the importance of behavioral cascading between connected users, there is little understanding of what factors could impact the likelihood of such cascades. To address this gap, we draw on the theory of competitive altruism to identify several moderators of behavioral cascading in eWOM. Our empirical tests using an online review dataset from Yelp show that eWOM cascading between a followee and a follower is less likely when the followee is a high-status member, a female, or has a strong connection with the follower; and more likely when the product in consideration is inexpensive. These findings provide valuable insights about the behavioral cascading process in eWOM and hold implications for social media platforms and sellers to facilitate the cascades of eWOM between connected consumers.

Decorrelated empirical likelihood for generalized linear models with high-dimensional longitudinal data

This paper focuses on decorrelated empirical likelihood-based inference for longitudinal data with ultrahigh-dimensional covariates. The primary issues we aim to address involve parameter estimation and hypothesis testing for a low-dimensional parameter of interest. Under the framework of the generalized linear model, we initially consider the within-subject correlation by linearizing the precision matrix with certain known matrices, which retains optimality even if the working correlated structure is misspecified. Coupled with the decorrelated matrix, we then eliminate the influence of nuisance parameters on the estimation procedure. The proposed approach not only yields more efficient estimators compared to generalized decorrelated estimating equations but also shares the same asymptotic variance as quadratic decorrelated inference function based methods. Furthermore, we define the decorrelated empirical log-likelihood ratio test statistic to assess the significance of regression coefficients. Finally, to evaluate the performance of the proposed procedure, we conduct simulation studies and apply it to a real data example.

Can asymmetry, long memory, and current return information improve crude oil volatility prediction? ——Evidence from ASHARV-MIDAS model

We propose an ASHARV-MIDAS model that incorporates the asymmetric and long-memory characteristics of financial asset returns, while integrating current return information into the volatility equation to enhance prediction accuracy. Additionally, we derive the lag order expression and conditional variance of short-term volatility in the novel model to analyze its distinction from the classical GARCH-MIDAS model that does not consider current return information. Empirical and robustness tests demonstrate superior in-sample parameter estimation performance and more precise out-of-sample volatility prediction capabilities of our proposed model.

Empirical Bayes Likelihood for Distrubition Family Based on Ranked Set Sampling

In empirical likelihood methods, the key to constructing a likelihood function is to find a suitable weight scheme that reflects the importance of data. These weights are usually limited by some constraints. By maximizing this likelihood function, we can obtain estimates of the parameters and perform corresponding hypothesis tests, In this paper, we get the empirical Bayes likelihood test rules for distribution based on ranked set sampling. Its asymptotic optimality is obtained.

Stretched sapwood, ultra-widening permeability, and ditching da Vinci: revising models of plant form and function.

The mechanisms leading to dieback and death of trees under drought remains unclear. For constructing an understanding of these mechanisms, addressing major empirical gaps regarding tree structure-function relations remains essential. We give reasons to think that a central factor shaping plant form and function is selection favoring both constant leaf specific conductance with height growth and isometric (1:1) scaling between leaf area and the volume of metabolically active sink tissues ("sapwood"). Sapwood volume-leaf area isometry implies that per-leaf area sapwood volumes become transversely narrower with height growth; we call this "stretching." Stretching means that selection must favor increases in permeability above and beyond that afforded by tip-to-base conduit widening (ultra-widening permeability), as via fewer and wider vessels or tracheids with larger pits or larger margo openings. Leaf area-metabolically active sink tissue isometry would mean that it is unlikely that larger trees die during drought because of carbon starvation due to greater sink-source relationships as compared to shorter plants. Instead, increase in permeability is most plausibly associated with greater risk of embolism, and this seems a likelier culprit of the preferential vulnerability of larger trees to climate change-induced drought. Other implications of selection favoring constant per-leaf area sapwood construction and maintenance costs are departure from the da Vinci rule expectation of similar sapwood areas across branching orders, and that extensive conduit furcation in the stem seems unlikely. Because all of these considerations impact the likelihood of vulnerability to hydraulic failure versus carbon starvation, both implicated as key suspects in forest mortality, we suggest that these predictions represent essential priorities for empirical testing.

Artificial intelligence and outward foreign direct investment: Evidence from China

We investigate the impacts of robot adoption (a representative form of artificial intelligence) on outward foreign direct investment (OFDI) by firms in China. First, we construct a unique firm-level dataset of A-share listed firms and conduct empirical analysis by adopting a staggered difference-in-differences (DID) strategy. Second, we find that changes in robot adoption on both the extensive and intensive margins encourage firms to conduct more OFDIs. Specifically, robot adoption has positive effects on multidimensional categories of OFDI but has no significant impact on buying OFDI. Third, we explore the underlying mechanism to show that the rise in output and growth of total factor productivity (TFP) matter. Fourth, we conduct a series of empirical tests to check robustness and obtain consistent results. Finally, we analyze the heterogeneous effects and find that adoption firms with state-owned ownership or higher profit tend to send more OFDI projects, especially to the Organization for Economic Co-operation and Development (OECD)-rich countries. Our findings elucidate the impact of robot adoption on OFDI at the firm level in developing and transition countries.

Accelerated construction of projection-based reduced-order models via incremental approaches

We present an accelerated greedy strategy for training of projection-based reduced-order models for parametric steady and unsteady partial differential equations. Our approach exploits hierarchical approximate proper orthogonal decomposition to speed up the construction of the empirical test space for least-square Petrov–Galerkin formulations, a progressive construction of the empirical quadrature rule based on a warm start of the non-negative least-square algorithm, and a two-fidelity sampling strategy to reduce the number of expensive greedy iterations. We illustrate the performance of our method for two test cases: a two-dimensional compressible inviscid flow past a LS89 blade at moderate Mach number, and a three-dimensional nonlinear mechanics problem to predict the long-time structural response of the standard section of a nuclear containment building under external loading.

The Link Between Social-Ecological Network Fit and Outcomes: A Rare Empirical Assessment of a Prominent Hypothesis

It is often claimed that the structure of networks influences outcomes in environmental governance. For example, network motifs of social-ecological fit have been linked to positive environmental outcomes, but empirical tests of this link are rare. Social-ecological network fit represents a situation in which actors involved in the governance and management of linked ecological elements coordinate. We empirically analyze how motifs of social-ecological network fit are associated with actors’ outcome assessments in ten cases of Swiss wetlands governance. We combine social networks among organizational actors, networks of interrelated ecosystem management activities, and actors’ assessments of outcomes. Results show that – contrary to the prominent theoretical claim – more fit is linked to worse outcomes. Drawing on the so-called risk hypothesis, we argue that our negative findings likely highlight a complicated causal process between actors’ assessments of outcomes and their adjustment to risks through coordination in networks.

Social Acceptance Scale—development of an instrument for the differentiated measurement of social acceptance in agricultural livestock farming

AbstractThis paper presents the development and validation of the Social Acceptance Scale (SAS), an instrument designed to measure social acceptance, particularly in transformative sectors like agricultural livestock farming. Recognizing the need for a nuanced acceptance scale, various facets of acceptance across a three-level continuum were delineated, spanning from opposition to commitment, encompassing eight distinct items. The SAS's creation and validation process included the conceptual and empirical testing of four validity types: content validity, face validity, construct validity, and criterion validity. Content and face validity involved construct definition, item generation, iterative review, and pilot testing to ensure theoretical soundness. Empirical testing encompassed construct validity through statistical validation and assessments of factorial and convergent validity. Furthermore, criterion validity was explored by examining associations with related constructs, enhancing the SAS's external applicability. In conclusion, this paper introduces the SAS as a tool to measure social acceptance within transformative sectors. It underscores the necessity for a comprehensive acceptance scale, offering a detailed account of its development and validation. The discussion section acknowledges limitations and outlines potential directions for future research in this domain.

Do traumatic events and substance use co-occur during adolescence? Testing three causal etiologic hypotheses.

Why do potentially traumatic events (PTEs) and substance use (SU) so commonly co-occur during adolescence? Causal hypotheses developed from the study of posttraumatic stress disorder (PTSD) and substance use disorder (SUD) among adults have not yet been subject to rigorous theoretical analysis or empirical tests among adolescents with the precursors to these disorders: PTEs and SU. Establishing causality demands accounting for various factors (e.g. genetics, parent education, race/ethnicity) that distinguish youth endorsing PTEs and SU from those who do not, a step often overlooked in previous research. We leveraged nationwide data from a sociodemographically diverse sample of youth (N = 11,468) in the Adolescent Brain and Cognitive Development Study. PTEs and substance use prevalence were assessed annually. To account for the many pre-existing differences between youth with and without PTE/SU (i.e. confounding bias) and provide rigorous tests of causal hypotheses, we linked within-person changes in PTEs and SU (alcohol, cannabis, nicotine) across repeated measurements and adjusted for time-varying factors (e.g. age, internalizing symptoms, externalizing symptoms, and friends' use of substances). Before adjusting for confounding using within-person modeling, PTEs and SU exhibited significant concurrent associations (βs = .46-1.26, ps < .05) and PTEs prospectively predicted greater SU (βs = .55-1.43, ps < .05) but not vice versa. After adjustment for confounding, the PTEs exhibited significant concurrent associations for alcohol (βs = .14-.23, ps < .05) and nicotine(βs = .16, ps < .05) but not cannabis (βs = -.01, ps > .05) and PTEs prospectively predicted greater SU (βs = .28-.55, ps > .05) but not vice versa. When tested rigorously in a nationwide sample of adolescents, we find support for a model in which PTEs are followed by SU but not for a model in which SU is followed by PTEs. Explanations for why PTSD and SUD co-occur in adults may need further theoretical analysis and adaptation before extension to adolescents.

AI-Generated Draft Replies Integrated Into Health Records and Physicians’ Electronic Communication

Timely tests are warranted to assess the association between generative artificial intelligence (GenAI) use and physicians' work efforts. To investigate the association between GenAI-drafted replies for patient messages and physician time spent on answering messages and the length of replies. Randomized waiting list quality improvement (QI) study from June to August 2023 in an academic health system. Primary care physicians were randomized to an immediate activation group and a delayed activation group. Data were analyzed from August to November 2023. Access to GenAI-drafted replies for patient messages. Time spent (1) reading messages, (2) replying to messages, (3) length of replies, and (4) physician likelihood to recommend GenAI drafts. The a priori hypothesis was that GenAI drafts would be associated with less physician time spent reading and replying to messages. A mixed-effects model was used. Fifty-two physicians participated in this QI study, with 25 randomized to the immediate activation group and 27 randomized to the delayed activation group. A contemporary control group included 70 physicians. There were 18 female participants (72.0%) in the immediate group and 17 female participants (63.0%) in the delayed group; the median age range was 35-44 years in the immediate group and 45-54 years in the delayed group. The median (IQR) time spent reading messages in the immediate group was 26 (11-69) seconds at baseline, 31 (15-70) seconds 3 weeks after entry to the intervention, and 31 (14-70) seconds 6 weeks after entry. The delayed group's median (IQR) read time was 25 (10-67) seconds at baseline, 29 (11-77) seconds during the 3-week waiting period, and 32 (15-72) seconds 3 weeks after entry to the intervention. The contemporary control group's median (IQR) read times were 21 (9-54), 22 (9-63), and 23 (9-60) seconds in corresponding periods. The estimated association of GenAI was a 21.8% increase in read time (95% CI, 5.2% to 41.0%; P = .008), a -5.9% change in reply time (95% CI, -16.6% to 6.2%; P = .33), and a 17.9% increase in reply length (95% CI, 10.1% to 26.2%; P < .001). Participants recognized GenAI's value and suggested areas for improvement. In this QI study, GenAI-drafted replies were associated with significantly increased read time, no change in reply time, significantly increased reply length, and some perceived benefits. Rigorous empirical tests are necessary to further examine GenAI's performance. Future studies should examine patient experience and compare multiple GenAIs, including those with medical training.