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The Balkan chamois (Rupicapra rupicapra balcanica) is a caprine of the rocky mountain slopes, threatened in Greece by illegal hunting and population isolation. We used a contingent valuation method to assess the willingness to pay (WTP) for chamois conservation of 500 residents of the region of Eastern Macedonia and Thrace. Most of the participants (61.6%) were WTP a mean of EUR 41.6 for chamois conservation, totaling EUR 6.03 million for the target population. Attitudes toward and knowledge about chamois, moralistic worldviews (spiritual reverence and ethical concern for nature and wildlife), participation in wildlife-related consumptive outdoor activities (i.e., hunting and fishing), intention to participate in conservation actions for the species, and encounters with the species in the wild were positively associated with WTP for its conservation. Dominionistic worldviews (humans have mastery, physical control, and dominance of wildlife) were negatively associated with WTP, while highly educated females with high income were more WTP for implementing relevant conservation actions. Factors involving previous knowledge of the chamois positively influenced the WTP, thus, confirming the construct’s bias toward charismatic species. The findings show that Greek residents highly value the chamois and its conservation and would be useful for advising this process and achieving its conservation management.

In the context of research on human judgment, regression is commonly treated as an artifact or an unwanted consequence of ill-controlled research designs. We argue that this negative image is undeserved. Regression affords not only an enlightening statistical construct but also a theoretical construct that can inspire novel research. It offers alternative accounts for a variety of well-known judgment biases, and it has inspired novel predictions of previously unknown biases. While all judgments that are less than perfectly correlated with a conditional variable must be regressive, systematic biases arise when different judgment targets are subject to unequally strong regression effects. This occurs when the information given about different targets varies in statistical uncertainty or extremity, the two determinants of regression. We illustrate the explanatory power of the regression construct for judgment biases in three paradigms: frequency estimations, performance evaluations, and illusory correlations. Because regression is a universal property of the empirical world, explanations of biases in terms of cognitive or motivational biases are insufficient and incomplete if the impact of regression is not taken into account.

Abstract Introduction: Little is known about how well sleep apps are grounded in behavioral theory. Additionally, limited research exists on whether apps that reflect behavioral constructs influence sleep behavior. Methods: A validated instrument was used to assign a behavioral construct score to a commercially available sleep app. The score was based on features of the app that encouraged realistic goal setting, self-monitoring, and other behavioral constructs related to sleep behavior. Data from approximately 4000 users across 32 countries were made available to analyze total daily sleep time. However, users without 5 days of sleep data, and less than 5 users per country were eliminated for a final sample of 213 users and 4600 unique daily entries on wake and sleep times. Results: The sleep app was assigned a behavioral construct score of 40 out of 100 possible points. The final sample consisted of users from 10 countries: Australia, Belarus, Canada, France, Germany, Great Britain, Russia, Spain, Ukraine, and the United States. The average sleep time across all countries was 6.9 hours (95% CI, 3.5, 10.9), and users in four countries reported less than the recommended 7 hours of sleep per night. Users in France reported the least amount of sleep (6.02 hours, 95% CI, 4.3, 8.2) while users in Belarus reported the most sleep (7.3 hours, 95% CI, 6.3, 8.3). Conclusion: Sleep apps with low behavioral construct scores may not encourage healthy sleep behaviors. However, additional comparisons with high scoring apps are needed to determine whether integrating behavioral constructs in sleep apps influence sleep time among adults. Support (If Any): This work was supported by research funds from the Department of Kinesiology and Community Health at the University of Illinois at Urbana Champaign.

The emotional state of being moved, though frequently referred to in both classical rhetoric and current language use, is far from established as a well-defined psychological construct. In a series of three studies, we investigated eliciting scenarios, emotional ingredients, appraisal patterns, feeling qualities, and the affective signature of being moved and related emotional states. The great majority of the eliciting scenarios can be assigned to significant relationship and critical life events (especially death, birth, marriage, separation, and reunion). Sadness and joy turned out to be the two preeminent emotions involved in episodes of being moved. Both the sad and the joyful variants of being moved showed a coactivation of positive and negative affect and can thus be ranked among the mixed emotions. Moreover, being moved, while featuring only low-to-mid arousal levels, was experienced as an emotional state of high intensity; this applied to responses to fictional artworks no less than to own-life and other real, but media-represented, events. The most distinctive findings regarding cognitive appraisal dimensions were very low ratings for causation of the event by oneself and for having the power to change its outcome, along with very high ratings for appraisals of compatibility with social norms and self-ideals. Putting together the characteristics identified and discussed throughout the three studies, the paper ends with a sketch of a psychological construct of being moved.

PurposeThe purpose of this paper is to propose and empirically test intellectual capital (IC) as a mediator in the corporate social responsibility (CSR) and financial performance (FP) relationship.Design/methodology/approachThe empirical research was conducted on 345 European firms listed in the STOXX Europe 600 index. To evaluate the mediating effect of IC, we applied the four-step Baron and Kenny model, tested through an ordinary least squares regression analysis.FindingsThe findings highlighted a partial mediation of IC on the CSR–FP relationship, suggesting that the implementation of CSR strategies has a positive effect on the development of firms' IC, which in turn enhances firms' competitive advantage and superior long-term FPs.Originality/valueWe found a new mediator in the CSR–FP relationship and we contribute to a new line of research that aims to study environmental and sustainability aspects strictly interrelated with IC and performances (sustainable intellectual capital).

Mobile ecological momentary assessment (mEMA) permits real-time capture of self-reported participant behaviors and perceptual experiences. Reporting of mEMA protocols and compliance has been identified as problematic within systematic reviews of children, youth, and specific clinical populations of adults. This study aimed to describe the use of mEMA for self-reported behaviors and psychological constructs, mEMA protocol and compliance reporting, and associations between key components of mEMA protocols and compliance in studies of nonclinical and clinical samples of adults. In total, 9 electronic databases were searched (2006-2016) for observational studies reporting compliance to mEMA for health-related data from adults (>18 years) in nonclinical and clinical settings. Screening and data extraction were undertaken by independent reviewers, with discrepancies resolved by consensus. Narrative synthesis described participants, mEMA target, protocol, and compliance. Random effects meta-analysis explored factors associated with cohort compliance (monitoring duration, daily prompt frequency or schedule, device type, training, incentives, and burden score). Random effects analysis of variance (P≤.05) assessed differences between nonclinical and clinical data sets. Of the 168 eligible studies, 97/105 (57.7%) reported compliance in unique data sets (nonclinical=64/105 [61%], clinical=41/105 [39%]). The most common self-reported mEMA target was affect (primary target: 31/105, 29.5% data sets; secondary target: 50/105, 47.6% data sets). The median duration of the mEMA protocol was 7 days (nonclinical=7, clinical=12). Most protocols used a single time-based (random or interval) prompt type (69/105, 65.7%); median prompt frequency was 5 per day. The median number of items per prompt was similar for nonclinical (8) and clinical data sets (10). More than half of the data sets reported mEMA training (84/105, 80%) and provision of participant incentives (66/105, 62.9%). Less than half of the data sets reported number of prompts delivered (22/105, 21%), answered (43/105, 41%), criterion for valid mEMA data (37/105, 35.2%), or response latency (38/105, 36.2%). Meta-analysis (nonclinical=41, clinical=27) estimated an overall compliance of 81.9% (95% CI 79.1-84.4), with no significant difference between nonclinical and clinical data sets or estimates before or after data exclusions. Compliance was associated with prompts per day and items per prompt for nonclinical data sets. Although widespread heterogeneity existed across analysis (I >90%), no compelling relationship was identified between key features of mEMA protocols representing burden and mEMA compliance. In this 10-year sample of studies using the mEMA of self-reported health-related behaviors and psychological constructs in adult nonclinical and clinical populations, mEMA was applied across contexts and health conditions and to collect a range of health-related data. There was inconsistent reporting of compliance and key features within protocols, which limited the ability to confidently identify components of mEMA schedules likely to have a specific impact on compliance.

Background/Objectives: Large language models (LLMs) have shown significant potential to transform various aspects of healthcare. This review aims to explore the current applications, challenges, and future prospects of LLMs in medical education, clinical decision support, and healthcare administration. Methods: A comprehensive literature review was conducted, examining the applications of LLMs across the three key domains. The analysis included their performance, challenges, and advancements, with a focus on techniques like retrieval-augmented generation (RAG). Results: In medical education, LLMs show promise as virtual patients, personalized tutors, and tools for generating study materials. Some models have outperformed junior trainees in specific medical knowledge assessments. Concerning clinical decision support, LLMs exhibit potential in diagnostic assistance, treatment recommendations, and medical knowledge retrieval, though performance varies across specialties and tasks. In healthcare administration, LLMs effectively automate tasks like clinical note summarization, data extraction, and report generation, potentially reducing administrative burdens on healthcare professionals. Despite their promise, challenges persist, including hallucination mitigation, addressing biases, and ensuring patient privacy and data security. Conclusions: LLMs have transformative potential in medicine but require careful integration into healthcare settings. Ethical considerations, regulatory challenges, and interdisciplinary collaboration between AI developers and healthcare professionals are essential. Future advancements in LLM performance and reliability through techniques such as RAG, fine-tuning, and reinforcement learning will be critical to ensuring patient safety and improving healthcare delivery.

Purpose The purpose of this paper is to elucidate the emerging landscape of procurement analytics. This paper focuses on the following questions: what are the current and future state of procurement analytics?; what changes in the procurement process will be required to enable integration of analytical solutions?; and what future areas of research arise when considering the future state of procurement analytics? Design/methodology/approach This paper employs a qualitative approach that relies on three sources of information: executive interviews, a review of current and emerging technology platforms and a small survey of subject matter experts in the field. Findings The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years. However, there currently exists a low usage of advanced procurement analytics, and data integrity and quality issues are preventing significant advances in analytics. This study identifies the need for organizations to establish a coherent approach to collection and storage of trusted organizational data that build on internal sources of spend analysis and contract databases. In addition, current ad hoc approaches to capturing unstructured data must be replaced by a systematic data governance strategy. An important element for organizations in this evolution is managing change and the need to nourish an analytic culture. Originality/value While the majority of forward-looking research and reports merely project broad technological impact of cognitive analytics and big data, much of it does not provide specific insights into functional impacts such as the impact on procurement. The analysis of this study provides us with a clear view of the potential for business analytics and cognitive analytics to be employed in procurement processes, and contributes to development of related research topics for future study. In addition, this study suggests detailed implementation strategies of emerging procurement technologies, contributing to the existing body of the literature and industry reports.

Purpose Recent reviews of field experiments aiming to entice tourists to behave in more environmentally sustainable ways conclude that attitudes – while the primary target – do not perform as well as expected. The purpose of this study is to analyse in detail when attitudes have or have not been successful as behavioural change targets and propose a conceptual framework of possible explanations. In so doing, this study represents the first theoretical – rather than empirical – challenge to the currently dominant theoretical understanding of environmentally significant tourist behaviours and offers alternative theoretical constructs tourism researchers aiming to make tourists behave in more sustainable ways could investigate in future. Design/methodology/approach The authors investigate in detail experiments where attitude-based behavioural change approaches failed. Based on the insights from this analysis, the authors propose a conceptual framework offering five potential explanations. This study also discusses alternative theoretical constructs that could be used for behavioural change interventions. Findings The authors derive five potential explanations for why attitudes often fail to trigger behavioural change in the context of environmentally sustainable tourist behaviour: tourists do not notice messages attempting to change their attitudes; tourists are unwilling to cognitively process behavioural change messages; tourists develop reactance to behavioural change requests; attempts to alter attitudes do not influence habits; and attempts to alter attitudes do not reduce the effort associated with displaying the desired behaviour. Research limitations/implications This study broadens research attention to alternative theoretical constructs that may be more effective in making tourists behave in more sustainable ways and opens opportunities for new measures tourism businesses and destinations can implement to influence tourist behaviour. Originality/value To the best of the authors’ knowledge, this is the first theoretical investigation of possible reasons why attitudes have performed poorly as targets of behavioural change interventions aiming to trigger environmentally sustainable tourist behaviours.

Background There is a well-recognized need for greater use of theory to address research translational gaps. Normalization Process Theory (NPT) provides a set of sociological tools to understand and explain the social processes through which new or modified practices of thinking, enacting, and organizing work are implemented, embedded, and integrated in healthcare and other organizational settings. This review of NPT offers readers the opportunity to observe how, and in what areas, a particular theoretical approach to implementation is being used. In this article we review the literature on NPT in order to understand what interventions NPT is being used to analyze, how NPT is being operationalized, and the reported benefits, if any, of using NPT. Methods Using a framework analysis approach, we conducted a qualitative systematic review of peer-reviewed literature using NPT. We searched 12 electronic databases and all citations linked to six key NPT development papers. Grey literature/unpublished studies were not sought. Limitations of English language, healthcare setting and year of publication 2006 to June 2012 were set. Results Twenty-nine articles met the inclusion criteria; in the main, NPT is being applied to qualitatively analyze a diverse range of complex interventions, many beyond its original field of e-health and telehealth. The NPT constructs have high stability across settings and, notwithstanding challenges in applying NPT in terms of managing overlaps between constructs, there is evidence that it is a beneficial heuristic device to explain and guide implementation processes. Conclusions NPT offers a generalizable framework that can be applied across contexts with opportunities for incremental knowledge gain over time and an explicit framework for analysis, which can explain and potentially shape implementation processes. This is the first review of NPT in use and it generates an impetus for further and extended use of NPT. We recommend that in future NPT research, authors should explicate their rationale for choosing NPT as their theoretical framework and, where possible, involve multiple stakeholders including service users to enable analysis of implementation from a range of perspectives.