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Twitter users’ generated data, known as tweets, are now not only used for communication and opinion sharing, but they are considered an important source of trendsetting, future prediction, recommendation systems and marketing. Using network features in tweet modeling and applying data mining and deep learning techniques on tweets is gaining more and more interest.

In this paper, user interests are discovered from Twitter Trends using a modeling approach that uses network-based text data (tweets). First, the popular trends are collected and stored in separate documents. These data are then pre-processed, followed by their labeling in respective categories. Data are then modeled and user interest for each Trending topic is calculated by considering positive tweets in that trend, average retweet and favorite count.

The proposed approach can be used to infer users’ topics of interest on Twitter and to categorize them. Support vector machine can be used for training and validation purposes. Positive tweets can be further analyzed to find user posting patterns. There is a positive correlation between tweets and Google data.

The results can be used in the development of information filtering and prediction systems, especially in personalized recommendation systems.

Twitter microblogging platform offers content posting and sharing to billions of internet users worldwide. Therefore, this work has significant socioeconomic impacts.

This study guides on how Twitter network structure features can be exploited in discovering user interests using tweets. Further, positive correlation of Twitter Trends with Google Trends is reported, which validates the correctness of the authors’ approach.

Information behaviour exists in two forms: first when information is sought with a clear purpose and second, when we encounter it accidentally or serendipitiously. The purpose of this paper is to estimate the information encountering (IE) and encountered information sharing (EIS) behaviour of research students in an online environment.

The quantitative research approach was applied to carry out this research. The authors selected 120 MPhil and PhD research students (who research information as a part of their assignments) from six departments as sample for the study. Out of 120 research students, 93 returned the filled questionnaires. The collected data were analysed in SPSS version 22. First, descriptive statistics to estimate the IE and sharing behaviour; and later one-way ANOVA and post hoc comparisons using the Tukey HSD tests were applied to investigate the EIS based on the frequency of internet usage.

The findings indicate that the mean scores of the responses remain between “sometimes” and “often”, in all the behavioural sub-constructs of the model of IE, i.e. noticing, stopping, examining, capturing, storing (keeping), sharing and returning. The extended model proved to be valid in an online environment in the context of Pakistani culture. While estimating EIS, the results indicated significantly higher sharing and large effect size among the research students who used the internet from 11 to 15 h a week than those who used it between 6 and 10 h.

Keeping in view the results the research students and parent organisations (universities) working for the improvement of research ranking and research students’ better performance, should know that research information is not only actively acquired but also huge amount of information is accidentally encountered and shared. Therefore, the universities should train their research students to enhance the information sharing of encountered information. That will promote the research culture and may enhance the speed of learning, research work and ultimately result in competitive advantage, without any extra effort.

This is the first study of its type in Pakistan to measure the IE behaviour of research students in an online environment. Moreover, it is the first study which investigates the extended model of IE using a quantitative approach in the Pakistani research environment, which originated in Japan via qualitative research approach.

This paper introduces a Bayesian two-sided group chain sampling plan (BT-SGChSP) by using binomial distribution to estimate the average proportion of defectives. In this Bayesian approach, beta distribution is used as a suitable prior of binomial distribution. The proposed plan considers both consumer's and producer's risks. Currently, group chain sampling plans only consider the consumer's risk and do not account for the producer's risk. All existing plans are used to estimate only a single point, but this plan gives a quality region for the pre-specified values of different design parameters. In other words, instead of point wise description for the designing of sampling plan based on a range of quality by involving a novel approach called quality region.

The methodology is based on five phases, which are (1) operating procedure, (2) derivation of the probability of lot acceptance, (3) constructing plans for given acceptable quality level (AQL) and limiting quality level (LQL), (4) construction of quality intervals for BT-SGChSP and (5) selection of the sampling plans.

The findings show that the operating characteristic (OC) curve of BT-SGChSP is more ideal than the existing Bayesian group chain sampling plan because the quality regions for BT-SGChSP give less proportion of defectives for same consumer's and producer's risks.

There are four limitations in this study: first is the use of binomial distribution when deriving the probability of lot acceptance. Alternatively, it can be derived by using distributions such as Poisson, weighted Poisson and weighted binomial. The second is that beta distribution is used as prior distribution. Otherwise, different prior distributions can be used like: Rayleigh, exponential and generalized exponential. The third is that we adopt mean as a quality parameter, whereas median and other quintiles can be used. Forth, this paper considers probabilistic quality region (PQR) and indifference quality region (IQR).

The proposed plan is an alternative of traditional group chain sampling plans that are based on only current lot information. This plan considers current lot information with preceding and succeeding lot and also considers prior information of the product.

This paper first time uses a tight (three acceptance criteria) and introduces a BT-SGChSP to find quality regions for both producer's and consumer's risk.

To be successful in the rapidly changing global business environment, supply chains (SCs) must be agile, adaptable and aligned (Lee, 2004), a practice known as Triple-A. Therefore, the purpose of this paper is to investigate the dimensions of Triple-A SCs and their concurrent impact on all three Triple-A components.

The relationship among these factors is analyzed through Smart PLS-structured equation modeling (PLS-SEM) for which data have been collected from 243 SC professionals working in manufacturing organizations.

The findings of this study reveal that the relationship between visibility and adaptability are directly significant but that the negative relationship between velocity and alignment is insignificant; however, indirectly these relationships have a positive impact using the mediating effect of agility over visibility and adaptability, velocity and alignment. However, the relationship of flexibility over SC Triple-A is positively significant, visibility over agility and alignment is positively significant and velocity over agility and adaptability is also positively significant, and each impact agility over adaptability and adaptability over alignment which is significant.

There is a shortage of empirical studies to date that empirically provide evidence of possible relationships among Triple-A and its key dimensions when attempting to obtain Triple-A. This is the first authenticated Triple-A SC conceptual framework that provides direction to better understand the dimension and significance of Triple-A.

The purpose of this study is to explore the determinants of needle stick injuries (NSIs) suffering in terms of occupational health and safety (OHS) coverage critically for health-care workers’ rights in Pakistan.

This is a qualitative study involving the designing of a questionnaire followed by the World Health Organization’s NSI prevention assessment tool and nationally published reports covering health-care workers’ OHS rights protection. A total of 17 public and private hospitals were surveyed with a two-stage sampling method. Descriptive and inferential statistics (one-way analysis of variance with multiple comparison tests) were applied and significant results were discussed (p = 0.05 & p = 0.01). The results were discussed critically in the context of the OHS rights of health-care workers.

Analysis revealed the following significant relationships: job type and safety behavior; age group of health-care workers and safety management; injection usage per day and safety behavior; past year’s needle sticks injuries cases with safety behavior and occupational exposure; work shift and work experience with safety knowledge, safety awareness and work experience with safety management. It was also found there is no specific OHS law in the country for health-care workers.

This study is limited in terms of sampling size and quantification of NSI burden among health-care workers.

Improved OHS management practices among health-care workers can control NSIs that ultimately ensure their workplace OHS rights. Health-care workers need OHS coverage in terms of awareness about potential workplace hazards and job training accordingly. Findings from extensive studies of a similar kind can give useful policy directions for workplace health management in health-care setup at the national level.

This study highlights the importance of OHS coverage for health-care workers in hospitals. It reports different determinants of NSIs suffering causing health-care worker’s rights violations at the workplace in Pakistan.

The paper clarifies research gaps and future directions in building information modeling (BIM) research by analyzing research trends and publication patterns. It aims to (1) systematically categorize the vast array of BIM literature into coherent main topics, (2) identify the most and least explored areas and (3) propose directions for future research based on identified research gaps.

This study uses the Latent Dirichlet Allocation (LDA) method to manage large datasets and uncover hidden patterns in academic journals and conference articles. To clarify the scholarly focus, the main topics in BIM research are categorized into three groups: (1) primary areas of focus, (2) moderately explored topics and (3) least investigated topics.

The findings revealed 10 main topics (MTs) and 57 subtopics (STs), identifying key areas such as project design and management (20%), innovative construction technology (14%) and sustainable construction/life cycle management (14%). Conversely, it also highlighted underexplored areas like Facility/safety management and urban data development, suitable for future research.

While this work provides a structured overview of the BIM domain, it reveals opportunities for further exploring the complexity of the interrelation among interdisciplinary topics.

The novelty of this study is its extensive scope, analyzing over fifteen thousand BIM articles from 2013 to 2023, which significantly expands the literature scale previously reviewed. This comprehensive approach maps BIM research trends and gaps and also shows the hierarchical trend line of publications in each main topic, setting a benchmark for future studies.

This paper aims to identify the unidimensionality and reliability of 84 factors that influence the performance of construction projects and develop a confirmatory factor analysis (CFA) model.

The study adopted a deductive research approach and started by identifying the positive factors that influence construction project performance. This was followed by the modification of the identified factors. After that, a questionnaire was developed out of the factors for data collection. Exploratory factor analysis was used to establish the factor structure of the positive factors, and this was verified using CFA afterwards. A model fit analysis was performed to determine the goodness of fit of the hypothesised model, followed by the development of the confirmatory model.

The study demonstrated substantial correlation in the data, sufficient unidimensionality and internal reliability. In addition, the estimated fit indices suggested that the postulated model adequately described the sample data.

The paper revealed that performance can be enhanced if stakeholders identify and leverage the positive factors influencing performance. The paper suggests that project stakeholders, particularly government, project owners, consultants and construction firms, can improve project performance by critically examining economic and financial systems (EFS), regulation and policy-making systems (RPS), effective management practices (EMP) and project implementation strategies (PIS).

The contribution of this paper to the present literature is identifying the positive factors and developing the confirmatory factor model. The model comprised 42 positive variables under four indicators: EMP, RPS, PIS and EFS.

This study aims to analyse the resilience strategy utilized by small and medium-sized enterprises (SMEs), enabling these businesses to effectively adapt their operations in response to varying conditions by providing them with essential resources. SMEs operate in marketplaces that are both dynamic and frequently tumultuous. These markets provide SMEs with a variety of obstacles, including economic ups and downs, advances in technology, evolving customer tastes and new regulatory requirements. SMEs need to create a strategic strategy to survive and grow in such situations. This strategy ought to help strengthen their resiliency and make it possible for them to make the most of emerging opportunities while simultaneously lowering the dangers.

The questionnaires adopted and adapted from previous research served as the basis for gathering the data. The manufacturing industry was polled through the use of questionnaires. To test the hypothesis, the data were analysed using Smart PLS. Through the use of closed-ended questions directed to the proprietors, managers or senior executives of SMEs, data were collected from each and every institution in the sample. Following the examination of the data by means of descriptive analysis and the presentation of several scenarios using information relating to SMEs, the findings were presented.

The ambidextrous strategies that are used by SMEs have a propensity to offer a constructive contribution to SMEs. In this study, it was discovered that ambidexterity, which is defined as the capacity to both seek and capitalise on possibilities, has a significant bearing on the organisational effectiveness of SMEs. The results showed that ambidextrous strategies have a propensity to work as mediators in interactions involving proactive resilience tactics and performance.

The research expands our understanding of how SMEs in the manufacturing sector may improve their performance by concentrating on growing their ambidextrous strategies.

This study provides a plausible explanation of two crucial management mechanisms for enhancing the sustainability of organisational effectiveness. The relationships between ambidextrous capabilities and firm effectiveness are malleable, and this study suggests that nurturing formal and informal relationships may be the key to SMEs' long-term sustainable performance. Improving the knowledge and performance of supply chain systems for SMEs in the manufacturing sector and boosting their competitiveness in domestic and international markets are the practical contributions of this study.

Our comprehension of monitoring, cooperation and innovation within social management was deepened as a result of these facts. In addition, the study conducted in the sector uncovered four essential connections that outline how managers should actively work towards lowering social risks, developing new possibilities and increasing business performance. These capacities and links, when taken as a whole, provide the foundation upon which an integrated framework and five research propositions are built.

This research offers a convincing explanation of fundamental management processes for enhancing the sustainability of organisational effectiveness. This research implies that developing formal and informal interactions may be the key to the sustainable performance of SMEs over the long run. The relationships between ambidextrous capabilities, methods and organisational effectiveness are flexible, and this study also suggests that these relationships may be shaped. The practical contributions made by this research include boosting the understanding and performance of supply chain systems for SMEs as well as the competitive power of these businesses in both local and international markets.

The purpose of this paper is to advance the theoretical perspective of complexity leadership paradigm to introduce shared leadership style as a precursor of taking charge behavior in public sector higher educational institutions (HEIs) of Pakistan. Moreover, this study unveils the underlying mechanisms of the climate of initiative and psychological safety for clarifying the link of shared leadership and taking charge.

The multi-source and multi-wave data were analyzed by employing double mediation analysis (PROCESS Model 4); using 282 valid responses obtained from a proportionate stratified sample of faculty members working in public sector HEIs of Pakistan.

The result indicates that shared leadership is a suitable style for governing the public sector HEIs and it fosters taking charge behavior in teaching faculty. Additionally, shared leadership creates climates that support initiatives and are psychologically safe that set stage for taking charge behaviors in teaching faculty of public sector HEIs of Pakistan.

This research has filled the gap of focusing on more collaborative leadership styles instead of traditional vertical leadership practices in public sector HEIs of Pakistan. Theoretically, this study suggests new insights into the contextual antecedents and mediating mechanisms of taking charge behaviors.