Search results

The purpose of this study is to examine how the interplay of stressor (e.g. fear of missing out, FoMO) and strains (e.g. perceived social overload, communication overload, information overload and system feature overload) in social networking sites (SNS) use can contribute to users’ SNS fatigue from a configurational view.

Data were collected among 363 SNS users in China via an online survey, and fuzzy-set qualitative comparative analysis (fsQCA) was applied in this study to scrutinize the different combinations of FoMO and overload that contribute to the same outcome of SNS fatigue.

Six combinations of casual conditions were identified to underlie SNS fatigue. The results showed that FoMO, perceived information overload and system feature overload are the core conditions that contribute to SNS fatigue when combined with other types of overloads.

The current work supplements the research findings on SNS fatigue by identifying the configurations contributing to SNS fatigue from the joint effects of stressor (FoMO) and strain (perceived social overload, communication overload, information overload and system feature overload) and by providing explanations for SNS fatigue from the configurational perspective.

The purpose of this two-part study is to systematically review, analyze and critically synthesize the current state of empirical research on knowledge loss induced by organizational member turnover (KLT).

This study is based on using a systematic literature review methodology reported in Part I.

Part II of this study contributes to the advancement of KLT scholarship by offering: an integrative narrative of KLT coping and preventive mechanisms as well as factors affecting them; an organizing framework of KLT empirical literature; and suggestions for future research, which are discussed with respect to the content, based on the proposed framework and by extending contextual dimensions of “who”, “where” and “when”, as well as use of theories and methods.

This study has limitations related to inclusion/exclusion criteria used for creating the review sample and the “Antecedents–Phenomenon–Outcomes” logic used to synthesize the findings.

Part II of this study offers a systematic synthesis of KLT empirical research with respect to KLT coping and preventive mechanisms and a discussion of opportunities for future research.

This study aims to identify the location of the micropyle, the role of the micropyle in seed germination and the association between the micropyle size and seed weight of grass peas.

First, the micropyle was identified by cutting the seed in half and observing the seeds under the electron microscope. Second, the micropyle was covered by lanolin to block water imbibition. The rate of imbibition and germination was then observed. Lastly, micropyle sizes of various grass pea genotypes were identified by capturing seed images under a light microscope and converting the sizes to mm² using computer software (ImageJ).

The location of micropyle was located nearby the hilum, similar to soybean seeds. Seed imbibition was significantly lower in lanolin application (<87%) than in the control (>124%) after 24 hours of submergence. Germination was a day delay for lanolin application on the micropyle compared to lanolin application on the non-micropyle. The germination delay resulted in a significantly lower germination percentage at <57% on the micropyle lanolin application than at >79% on the non-micropyle lanolin application after 10 days of sowing. There is no correlation between the micropyle size and seed weight.

These findings add information on the location and the role of the micropyle for grass pea seed germination.

Auditory hallucinations (“hearing voices”) are a relatively common experience, which is often highly distressing and debilitating. As mental health services are under increasing pressures, services have witnessed a transformative shift with the integration of technology into psychological care. This study aims to narratively synthesise evidence of technology-enhanced psychological assessment and treatment of distressing voices (PROSPERO 393831).

This review was carried out according to the preferred reporting items for systematic reviews and meta-analyses. Embase, MEDLINE, PsycINFO and Web of Science were searched until 30th May 2023. The Effective Public Health Practice Project (EPHPP) tool assessed methodological quality of studies.

Searching identified 9,254 titles. Fourteen studies (two assessment studies, twelve treatment studies, published 2010–2022, n = 1,578) were included in the review. Most studies were conducted in the UK, the USA or Canada. Technologies included avatar therapy, mobile apps, virtual reality, a computerised Web-based programme and a mobile-assisted treatment. Overall, technology-enhanced psychological assessments and treatments appear feasible, acceptable and effective, with avatar therapy the most used intervention. EPHPP ratings were “strong” (n = 8), “moderate” (n = 5) and “weak” (n = 1).

To the best of the authors’ knowledge, this is the first systematic review to investigate these technologies, specifically for distressing voices. Despite the relatively small number of studies, findings offer promising evidence for the clinical benefits of these technologies for enhancing mental health care for individuals with distressing voices. More high-quality research on a wider range of technologies is warranted.

The purpose of this two-part study is to systematically review, analyze and critically synthesize the current state of empirical research on knowledge loss induced by organizational member turnover (KLT).

A systematic literature review was conducted based on 91 empirical studies on KLT.

Part I of the study contributes to the advancement of KLT scholarship by mapping key developments in empirical research on KLT (publication trends, methodological and theoretical foci, heterogeneity of geographical, industrial and organizational contexts); encapsulating KLT antecedents associated with both voluntary and involuntary turnover; and revealing a broad scope of KLT effects at organizational and unit level.

This study has limitations related to inclusion/exclusion criteria used for creating the review sample and the “Antecedents–Phenomenon–Outcomes” logic used to synthesize the findings.

Part I of the study offers a systematic synthesis of KLT empirical research with respect to KLT antecedents, outcomes and factors affecting them.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.