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This study aims to test the mediating role of psychological contract (PC) in a relationship between personality dimensions and turnover intention.

The current study is analytical in nature. The data for the purpose of the analysis is collected from 300 software engineers working in Lahore, Punjab. Purposive sampling technique is used for the collection of this data. The response rate was 87.33 per cent. Different data analysis techniques such as correlation, regression analysis, are used to test the 10 hypotheses of the study. Moreover, the study adopted a cross-sectional survey design.

According to regression analysis, extroversion, conscientiousness and agreeableness personality dimensions brought positive but insignificant increments in turnover intention. However, emotionally stable personality dimensions brought positive and significant increments in turnover intention. Open to experience personality dimension brought negative but insignificant decrement in turnover intention. Results showed extroversion personality dimension brought a very less but insignificant increment in variations of PC, which have higher contributions in variations of turnover intention. Emotional stable, conscientiousness and agreeableness personality dimensions brought also very less but a significant increment in PC. Open to experience personality dimension have negative but insignificant decrement in PC. Results showed the mediation impact of PC among emotional stability, conscientiousness and agreeableness personality dimensions and turnover intention. However, PC does not mediate among extroversion, open to experience personality dimensions and turnover intention. The paper concludes with recommendations for further research.

This study will help the organization in reducing the turnover rate and can enhance the motivation level of their employees.

Background: Insurance was discovered many centuries before Christ (BC). In the second and third millennia BC, Chinese and Babylonian traders traded risks. Insurance is now the backbone of the economy, but penetration is low in developing countries. Big data, internet of things (IoT), and InsurTech have recently ushered in the fourth industrial revolution in insurance.

Objective: This study examines the Indian challenges and solutions of using Big Data Analytics (BDA).

methodology: A SLR was used to extract themes/variables related to challenges and solutions in adopting BDA in the Indian insurance sector. Google Scholar was searched for relevant literature using keywords. Inclusion and exclusion criteria were used to filter the studies.

Findings: This study identified several barriers to BDA adoption in the Indian insurance industry. Policymakers could use the suggestions to improve insurance service delivery.

Practical implication: Insurers can understand the challenges, and accordingly, they can adopt the proposed solution in this study to enhance the insurance penetration in India.

This study aims to investigate the impact of message framing (emotional vs rational) on social media users' ability to accurately detect information and their intention to share messages about the COVID-19 vaccine.

Using an experimental design approach, the authors recruited 600 adult participants via a crowdsourcing platform. Participants were randomly assigned to receive emotional or rational messages and their ability to accurately detect information and intention to share messages were assessed.

The results showed a significant multivariate effect of message framing on both the detection of accurate information and intention to share (p < 0.001). Participants who received emotional messages demonstrated better performance in the detection and sharing task than those who received rational messages. Gender and age also had significant main effects on the outcomes, with women performing better than men and younger participants performing better than older participants in detecting the accuracy of information. The interaction effects of the independent variables were not statistically significant (p = 0.098).

The findings highlight the importance of considering emotional factors in combating the spread of messages about the COVID-19 vaccine on social media. Practitioners responsible for social media content should strengthen the content review mechanism, with an emphasis on screening content with high emotional arousal.

This paper aims to examine the relationship between intra-organizational knowledge hiding (I-OKH) and turnover intention via the mediating role of organizational embeddedness.

A model was developed and tested with data collected from 276 knowledge workers from the Islamic Republic of Iran Broadcasting (IRIB) using Smart PLS3 to test the hypotheses.

Results show that organizational embeddedness mediates the relationship between intra-organizational knowledge hiding and turnover intention because intra-organizational knowledge hiding relates negatively to organizational embeddedness, which, in turn, has a negative effect on turnover intentions.

This study can be beneficial for organizations that employ knowledge workers. The management should pay attention to the existence and consequences of intra-organizational knowledge hiding to control one of the causing factors of weakened organizational embeddedness, which, in turn, increases employee turnover intentions.

This study is the first attempt to analyze knowledge hiding from a third-person point of view. Moreover, this is the first to examine the mediating role of organizational embeddedness in the relationship between intra-organizational knowledge hiding and employee turnover intentions, enriched by employing the data from the knowledge workers beyond the Anglo-American-European world.

Co-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige of the co-cited articles. Despite its quantitative nature, it is found effective in retrieving and evaluating documents, signifying its linkage with the related documents' contents. To better understand the dynamism of the citation network, the present study aims to investigate various content features giving rise to the measure.

The present study examined the interaction of different co-citation features in explaining the co-citation frequency. The features include the co-cited works' similarities in their full-texts, Medical Subject Headings (MeSH) terms, co-citation proximity, opinions and co-citances. A test collection is built using the CITREC dataset. The data were analyzed using natural language processing (NLP) and opinion mining techniques. A linear model was developed to regress the objective and subjective content-based co-citation measures against the natural log of the co-citation frequency.

The dimensions of co-citation similarity, either subjective or objective, play significant roles in predicting co-citation frequency. The model can predict about half of the co-citation variance. The interaction of co-opinionatedness and non-co-opinionatedness is the strongest factor in the model.

It is the first study in revealing that both the objective and subjective similarities could significantly predict the co-citation frequency. The findings re-confirm the citation analysis assumption claiming the connection between the cognitive layers of cited documents and citation measures in general and the co-citation frequency in particular.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-04-2020-0126.

The evolution of technologies has unleashed a wealth of challenges by generating massive amount of data. Recently, biological data has increased exponentially, which has introduced several computational challenges. DNA short read alignment is an important problem in bioinformatics. The exponential growth in the number of short reads has increased the need for an ideal platform to accelerate the alignment process. Apache Spark is a cluster-computing framework that involves data parallelism and fault tolerance. In this article, we proposed a Spark-based algorithm to accelerate DNA short reads alignment problem, and it is called Spark-DNAligning. Spark-DNAligning exploits Apache Spark ’s performance optimizations such as broadcast variable, join after partitioning, caching, and in-memory computations. Spark-DNAligning is evaluated in term of performance by comparing it with SparkBWA tool and a MapReduce based algorithm called CloudBurst. All the experiments are conducted on Amazon Web Services (AWS). Results demonstrate that Spark-DNAligning outperforms both tools by providing a speedup in the range of 101–702 in aligning gigabytes of short reads to the human genome. Empirical evaluation reveals that Apache Spark offers promising solutions to DNA short reads alignment problem.

Many printing ink manufacturers have switched to more environmentally friendly inks in recent years. Additionally, printing on food demands nearly the same level of care. Also, flexible smart ink aids in protecting the content from microbes and offers information on the content’s freshness.

The goal of this research is to develop a novel formulation based on natural resources to be printed on food. For food printing using the screen method, certain organic binders including starch, sodium alginate and Arabic gum as well as natural colors like red beet, black barberry and beetroot were used. To establish the formulation suitable for screen printing, rheological parameters were examined. In addition, to assess the color of the printed inks over 48 h period, samples underwent optical stability testing.

The tape test showed that all inks exhibit good adhesive characteristics. The outcomes demonstrated that cochineal has the highest optical stability among the dyes. Alginates and starch have greater rheological qualities than Arabic gum ink, another reason why it is not a viable choice for screen printing. The duration of color ink relative to time shows the appropriate possibility of using this ink as a sensor.

In general, the substance containing sodium alginate and starch as concentrator and beetroot as dye showed the optimum properties for food printing in this study.

Drawing from social capital theory, this study aims to investigate the manifested critical barriers in deriving and implementing gender diversity policies, paying particular attention to the role multiple directorships play in shaping the directors’ behavior and the dynamic of the board of directors. The study comprehends social capital as a multi-dimensional concept and uses combinations of interconnected internal, external, expressive and instrumental networks.

The study uses a mixed-method approach through which the quantitative approach is supplemented by a qualitative research method to comprehensively examine the development and impact of female directors’ networks in Australia. To do so, a large data set consisting of 2,527 observations of all Australian firms and data emerged from semi-structured interviews with female directors were brought together and analyzed.

The findings reveal an inverted U-shaped relationship between the size of women’s directorate networks and firm performance. The study additionally explicates the key moderating factors influencing the optimal number of multiple directorships. The key power-based and psychological well-being-related benefits of the inter- and intra-organizational interactions and “open” directorate networks for individual directors are further discussed. The findings also elucidate the status quo vis-à-vis labyrinth metaphor and excessive numbers of directorships.

The study should be of interest to those interested in effective gender diversity management. The findings would assist in enabling tangible outcomes for women through advanced processes and systematic investment in and institutionalization of well-structured, equitable opportunities provided via gender-responsive policies dedicated to the education and training of future female directors.

Calling for social dialogues and discussions on non-financial factors, this study adds to the scarce literature on influential factors related to diversity management policies and practices on the board of directors.

The aim of the paper is to present a preliminary study for the design of a new functional food by the incorporation of a collection of ingredients which are all based on an inexpensive by‐product of the food industries: apple pomace. The new product design was considered as a novel gelled dessert formulation which is functional, and totally nature‐based. In fact, the article reviews various raw materials obtainable from the source of apple pomace and gradually supports the hypothesis of such product design.

The current study was designed on the structural basis of paying attention to apple pomace as a byproduct and idea generation for product design, reviewing several ingredients based on apple pomace (available data from the literature) and discussing the suitability of such ingredients for a new functional product. Exclusive attention was made for the development of an apple‐pomace‐based gelled dessert targeting consumers on restricted diets such as diabetics and obese individuals. In these kinds of diets consumption of caloric sweeteners should be abandoned or decreased while increasing the amounts of dietary fibers and polyphenolic compounds can be health‐beneficial.

As an appropriate preliminary formula, amidated low methylester pectins were selected as gelling agents. High methylester pectins, phloridzin and quercetin were used as functional ingredients. Arabinose and fructose were considered as sweetening agents. Also, POPj (phloridzin oxidation product), which is a recently developed natural pigment, was offered as a colouring agent and citric acid for adjusting the pH. Apple specific flavours were also suggested to improve the consumer acceptance of the product. In each case, the evidences of functionalities considered for the target consumers (diabetics and obese individuals) were also discussed.

This fresh formula is novel and can attract both food industry and the consumers because of its natural and functional properties.