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Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

Building on the relationship marketing and stimulus-organism-response (SOR) theory, the purpose of this paper is to study the impact of the integrated store service quality (ISSQ) on the omnichannel customer lifetime value (CLV). The mediating role of customer commitment (affective, normative and continuance) and relationship program receptiveness with the moderating role of customer relationship proneness were relied upon to better understand the omnichannel customer profitability metric (CLV).

The study is descriptive and relies upon the cross-sectional data collected using the self-administered structured questionnaires from 785 omnichannel shoppers. A purposive sampling technique was performed in the study. Structural equation modeling was performed using the SMART-PLS 4.0 software to analyze the data.

The results indicate that omnichannel customer commitment (affective, normative and continuance) differentially mediates the relationship between ISSQ and relationship program receptiveness, subsequently impacting the omnichannel CLV. The customer relationship proneness significantly and positively moderated the relationships between different dimensions of customer commitment and relationship program receptiveness.

The study relied upon the cross-sectional data from the Indian population aged above 18 years for testing the proposed model. Further studies could test the model across different populations to generalize the study results.

This study addresses the need to investigate the omnichannel retail store customer profitability and their relationship performance with the store. By testing the customer relationship management model in the omnichannel retail store context, this study is the first to show that ISSQ will impact the customer profitability and relationship performance metric (CLV) through omnichannel customer commitment and relationship program receptiveness. The moderating effect of customer relationship proneness on a few proposed hypotheses was also tested to give managerial recommendations.

The purpose of this paper is to test the impact of selected characteristics of jobseekers on employers’ decisions regarding potential hires (direct and probabilistic signals). The main focus of the study is to test the impact of jobseekers’ participation in selected active labour market programmes on employers’ hiring decisions for three positions: unskilled worker, skilled worker and administrative employee. Other characteristics tested include age, gender, presence of children in the household, state of health, experience of short- and long-term unemployment and indebtedness.

This study analyses data from a representative survey of employers with five or more employees in the Czech Republic. The survey was conducted in December 2020 using stratified random sampling, combining online questionnaires and personal interviews. The study includes 1,040 employers and uses the factorial survey experiment (FSE) design.

The results of the FSE suggest that the perceived positive impact of completing one of the activation programmes depends on the position for which the candidate is being recruited. While for the unskilled job category, the completion of any of the tested schemes (training, subsidised jobs or public works) had a positive effect; for the skilled job category, only the training and subsidised jobs schemes had a positive effect; and for the administrative job category, public works programme even had a negative effect.

A somewhat limiting factor in the context of this study seems to be the definitions of the positions tested (unskilled and skilled workers and administrative staff). The decision-making of the respondents was somewhat restricted by such broadly defined categories. Typically, studies with FSE designs have a focus on a specific sector of the economy, which allows for a better definition of the positions or jobs under test. The relationship between position and the impact of individual characteristics is clearly a matter for further research.

The results of the study confirm that completion of the activation programme, as well as other candidate characteristics, constitute differentiating signals for employers that influence their hiring decisions. At the same time, there is evidence that the training programme and the subsidised jobs programme are effective in terms of increasing participants’ chances of employment.

The demand side should be included in the evaluation of activation policies. The design of the FSE provides an appropriate way to test the impact of activation measures on the decision-making of employers.

Given the complex nature of integrated care systems (ICSs), the geographical spread and the large number of organisations involved in partnership delivery, the importance of leadership cannot be overstated. This paper aims to present novel findings from a rapid realist review of ICS leadership in England. The overall review question was: how does leadership in ICSs work, for whom and in what circumstances?

Development of initial programme theories and associated context–mechanism–outcome configurations (CMOCs) were supported by the theory-gleaning activities of a review of ICS strategies and guidance documents, a scoping review of the literature and interviews with key informants. A refined programme theory was then developed by testing these CMOCs against empirical data published in academic literature. Following screening and testing, six CMOCs were extracted from 18 documents. The study design, conduct and reporting were informed by the Realist And Metanarrative Evidence Syntheses: Evolving Standards (RAMESES) training materials (Wong et al., 2013).

The review informed four programme theories explaining that leadership in ICSs works when ICS leaders hold themselves and others to account for improving population health, a sense of purpose is fostered through a clear vision, partners across the system are engaged in problem ownership and relationships are built at all levels of the system.

Despite being a rigorous and comprehensive investigation, stakeholder input was limited to one ICS, potentially restricting insights from varied geographical contexts. In addition, the recent establishment of ICSs meant limited literature availability, with few empirical studies conducted. Although this emphasises the importance and originality of the research, this scarcity posed challenges in extracting and applying certain programme theory elements, particularly context.

This review will be of relevance to academics and health-care leaders within ICSs in England, offering critical insights into ICS leadership, integrating diverse evidence to develop new evidence-based recommendations, filling a gap in the current literature and informing leadership practice and health-care systems.

This paper investigates how gender, ethnicity, and network membership interact to influence how small and medium-sized enterprise (SME) owner-managers become aware of finance support programmes developed by government policy and/or support schemes advanced by the banking industry.

Drawing on expectation states theory (EST), we develop eight sets of hypotheses and employ the UK SME Finance Monitor data to test them using bivariate probit regression analysis.

In general, network membership increases awareness, but more so for government programmes. We also find no differences between female and male owner-managers when in networks. However, we identify in-network and out-network differences by ethnicity, with minority females seemingly better off than minority males.

Business networks are better for disseminating government programmes than industry-led programmes. For native White women, network membership can enhance policy awareness advantage further, whilst for minorities, networks significantly offset the big policy awareness deficits minorities inherently face. However, policy and practice need to address intersectional inequalities that remain in access to networks themselves, information access within networks, and the significant out-network deficits in awareness of support programmes afflicting minorities.

This study provides one of the first large-scale empirical examinations of intersectional mechanisms in awareness of government and industry-led enterprise programmes. Our novel and nuanced findings advance our understanding of the ways in which gender and ethnicity interact with network dynamics in entrepreneurship.

The study’s aim was to design and test a leadership development approach using blended learning, to equip leaders for strengthening their own resilience and that of their teams.

A contextualised leadership development intervention was produced and evaluated following the principles of design-based research. Participants were from three organisations that work internationally to address the impact of economic disadvantage. Initial research used the behavioural event interview technique. Online assessment incorporated measures of situational judgement, emotion recognition and attributional style. Validity measures were multi-rater feedback (criterion), and NEO-PI 3 (construct). Individual feedback and a simulation-based peer workshop were followed by a four-to-six month period of experience-driven development and a final peer workshop for consolidating and evaluating learning outcomes.

The online assessment was a valid measure of leaders’ personal resilience resources and their resilience-building capability. Overall, the intervention improved participants’ understanding of, and engagement with, the processes of strengthening individual and collective (team) resilience.

The target sample size for the study was relatively small, to ensure it would be practical to replicate the approach when designing similar interventions for a senior leadership population in other contexts. Significant results provided robust evidence for the validity of the assessment approach. Findings for the workshops and experience-driven development phase were more tentative, but the value of the design iterations was clearly demonstrated.

The leadership development approach is suitable for application in other organisations, if similar principles are followed to produce and evaluate materials relevant to each broad sector context. Roll-out is cost-effective, with relatively few hours of blended or virtual delivery supporting experience-driven learning.

The impact leaders have on the wellbeing of those who report to them is well established, but less has been done to develop and formally evaluate practical, cost-effective interventions to improve this impact. The approach validated in this study can be applied more widely to benefit employee wellbeing as well as performance.

The study developed and evaluated a new approach to preparing leaders for the challenge of building team resilience, an aspect of leadership capability that has been given relatively little attention to date.

This study aims at investigating the effect of bolt hole-making processes on the post-fire behavior of S235 steel plates.

A total of nine steel plates with a single bolt hole are tested. The single bolt holes are fabricated using three different hole-making processes: drilling, waterjet and plasma. Among the nine steel plates, three fabricated specimens are control specimens and are tested at ambient temperature. The six remaining steel plates with a single bolt hole are subjected to a complete heating-cooling cycle and then monotonically loaded until failure. The six fabricated specimens are first heated up to two different temperatures 800 and 925 °C, and then cooled back to the ambient prior to loading.

The results show that after being exposed to post-fire temperatures (800 and 925 °C), the maximum decrease in strength of the S235 steel plate was 6% (at 925 °C), 14% (at 925 °C) and 22% (at 800 °C) when compared to the results of ambient specimens for waterjet, drilled and plasma bolt holes, respectively. For post-fire temperature tests, drilled and waterjet bolt hole-making processes result in having approximately the same load-displacement response, and both have larger strength and ductility than those obtained using plasma cutting.

This study provides preliminary data to guide the steel designers and fabricators in choosing the most suitable hole-making process for fire applications and to quantify the post-fire reduction in capacity of S235 plates.

This paper aims to provide an overview of a social marketing intervention that aimed to increase physical activity (aligned to UN SDG 3) among adolescents in Bali, Indonesia.

Three sequential phases were followed to deliver the social marketing intervention. Phrase 1 (formative research) gained insights that guided a subsequent social marketing intervention. Phase 2 (pilot intervention) gathered preliminary results, to support the development of the final intervention. Phase 3 (intervention) evaluated the effectiveness of the two-month social marketing intervention.

The results from the intervention tested in this paper identified significant behaviour change in physical activity, demonstrating the effectiveness of the intervention. Furthermore, the paper identifies which intervention inputs contribute to behaviour change and which do not.

This paper describes the outcomes from an eight-week pilot programme that aimed to increase rates of physical activity for Indonesian adolescents and provides early evidence of impact.

This study found that providing adolescents with the opportunity to play team sports increases physical activity behaviour.

There is a lot of ground that needs to be made in terms of designing programs capable of achieving impact in the Global South. The approach reported in this paper can serve as a best-practice model for researchers wanting to drive lasting behaviour change to overcome known inequities in the Global South.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.