Suchergebnisse

The phenomenon of law implementation has received limited attention, despite the clear evidence that it is influenced by various factors prevalent in the country, and these factors can have an impact on and obstruct the effective implementation of legislation. The primary objective of this study was to analyze the critical factors that impact the implementation of cybersecurity laws in developing nations, such as Pakistan. The prevalence of corruption, a major hindrance to the implementation of cybersecurity laws and regulations, emerged as the most influential factor in Pakistan. Additionally, factors such as discrimination, illicit conduct, expertise, ambiguity, and public confidence significantly influenced the implementation of cybersecurity laws in Pakistan. A survey was conducted among managers from banking and IT firms to collect data samples on the factors that could potentially impact the implementation of the law. The findings from a sample of 172 respondents revealed that corruption, discrimination, illicit conduct, and ambiguity appeared to have a significant negative influence on cybersecurity law implementation, whereas expertise and public confidence emerged to have a significant positive influence on the implementation of cybersecurity laws in Pakistan. This study suggests that the government of Pakistan should consider various measures such as providing training, improving capacity building, fostering institutional cooperation, strengthening legislative conviction, and promoting global collaborations to enhance the implementation of cybersecurity.

The goal of this study is to investigate the direct and indirect relationships that exist between artificial intelligence (AI), social innovation (SI), and smart decision-making (SDM). This study used a survey design and collected cross-sectional data from South Korea and Pakistan using survey questionnaires. Four hundred sixty respondents from the public and private sectors were obtained and empirically analyzed using SPSS multiple regression. The study discovered a strong and positive mediating effect of SI between the relationship of AI and SDM, as predicted. Previous researchers have investigated some of the factors that influence the decision-making process. This study adds to the social science literature by examining the impact of a mediating factor on decision-making. The findings of this study will contribute to the local government in building smart cities such that the factor of social innovations should be involved in the decision-making process because smart decision-making would share such collected data with entrepreneurs, businesses, and industries and would benefit society and all relevant stakeholders, including such social innovators.

Numerous segments of society have been affected by the global Covid-19 pandemic. It has heralded a new era oriented toward the digitization of Pakistan after the shutdown of public sector institutions and disruptions in governance implementations. The objective of this study is to investigate how governments' innovation initiatives enhance government response to cope with Covid-19 with the primitive mechanism of citizens' adoption intention behavior during the pandemic. Employing a structural equation model in SmartPLS, data samples collected from 663 followers of social media accounts of government information department through a self-administered survey questionnaire were examined. The findings indicated a direct and indirect relationship between governments' innovation initiatives and responsive e-governance, intending to adopt e-services acting as a mediator. Similarly, the quality of government information was found to influence citizens' willingness to adopt e-services by interacting with innovation initiatives. Institutions and policymakers can benefit from the study's strategic and practical recommendations.

Assigning homework to students make they are learning more effective and they comprehend the assigned task in depth by applying drill and practice activities. The current study examines the effects of assigning homework on the achievement of students at the primary level. The population of the study was 100 boys' primary schools. The sample respondents of the study were students of class 5th consist of a total of sixty students and each group such as experimental, comparison, and control group was twenty students. The experimental, comparison and control groups of the students were selected by the flipping of the coin as to which will be experimental, comparison, and the control group. The researcher adopted a simple random sampling technique. The data were collected through pre and post-standardized achievement tests based on mixed items (mix tests) developed by the researcher. The researcher developed fourteen lesson plans to teach the fourteen lessons. The pre and post standardized achievement tests were conducted, collected, and evaluated under the supervision of the researcher. Data were analyzed in the form of one-way ANOVA to find out the significant difference in f-value and p-value of the experimental, comparison, and control group regarding the 14 selected topics taught. The research concluded that there was no statistically significant difference in p-value and f-value in the achievement of the students in experimental, comparison, and control group from the lessons 1-6 due to repetition and diffusion in lessons and there was a statistically significant difference in p-value and f-value in experimental, comparison and control group from the lessons 7-14 taught. The data were presented in the form of tables.

An emerging voice of patients in the form of opinion and expectation about the quality of care has the potential for improvement in service quality. A large volume of patients' opinion as online doctor reviews are available online in order to access, analyze, and improve patients' perception. This paper aims to mine online doctor reviews to explore the different determinants of patient satisfaction and dissatisfaction toward the United Kingdom (U.K.) healthcare services with the two-factor theory. This study is based on the two-factor theory, in light of online doctor reviews from a prominent health rating website in the U.K (Iwantgreatcare.org), an improved text mining approach is proposed by introducing SenticNet to Latent Dirichlet Allocation (LDA) to analyze patients' healthcare experience. This method finds latent topics that create either patient satisfaction or dissatisfaction toward a healthcare system. We then calculate the patient satisfaction rate across each disease specialty. Then sentiment analysis was performed using the Hourglass of Emotions model to compute the polarity of each review sentence (positive, or negative). Next, the classification results reveal that the proposed model that analyzes patient opinion toward a different aspect of care outperformed other state-of-the-art models. Finally, a SWOT and root-cause analysis is performed to identify strengths, weaknesses, opportunities, and threats to a medical system. Our findings provide a clue for doctors, hospital, and government officials to enhance patient satisfaction and minimize dissatisfaction by satisfying their needs and improve the quality of care across different diseases. Key words: patient satisfaction; text mining; topic modeling; LDA; sentiment analysis.

PurposeThe latest mobile technology may shape consumers' motivations by allowing them to order a variety of foods using smartphone apps. Following the stimulus–organism–response (SOR) framework and using a mixed methods approach, this study investigates the impacts of different components of mobile dining on customers' perceived value, which leads to actual purchase intentions. Furthermore, this study examines the moderating effect of the restaurant type.Design/methodology/approachData were collected via an online questionnaire survey from 351 individuals in the city of Jakarta (Indonesia) who actually used mobile apps to order food online. Data analysis was carried out using structural equation modeling.FindingsThe findings reveal that source credibility, review valence, the navigation system, food quality and service quality significantly impact customers' perceived value. Customers' perceived value, in turn, positively affects their purchase intentions. The findings also reveal that the impacts of review valence, the navigation system, food quality and service quality on customers' perceived value depend on the different levels of restaurants.Originality/valueThis study is among the first in the mobile commerce research that studies the impacts of mobile electronic word-of-mouth (eWOM), system quality and overall restaurant image on dining choices by considering actual mobile shoppers. Second, this study extends the SOR model to examine the impact of the mobile environment-based characteristics on the perceived value that leads to purchase intentions. Third, the current study examines whether the relationships that are discussed early on differ based on the restaurant type. The findings of this study could help practitioners achieve a deeper understanding of diners' behaviors due to the perceived benefits of mobile dining.

PurposeWith a foundation in the conservation of resource theory, this paper aims to examine the validity of a conceptual model that explains the mechanism connecting perceived threat of terrorism to production deviance. The link between perceived threat of terrorism and production deviance was examined via emotional exhaustion. Notably, the study evaluated whether the relationship between perceived threat of terrorism and production deviance is mediated by emotional exhaustion and moderated by levels of emotional intelligence.Design/methodology/approachThe study is cross-sectional in nature and data were collected from 432 pharmaceutical sales representatives who operate outdoors in the high-risk region. Two-step approach consisting confirmatory factor analysis and structural equation modeling was used for analysis. To examine conditional direct and indirect effects, the authors used model 8 in PROCESS.FindingsResults were consistent with prediction made from the conceptual model in that emotional exhaustion partially mediated the relationship between perceived threat of terrorism and production deviance. This was particularly the case when emotional intelligence was low, but not when high. Likewise, perceived threat of terrorism exerted a direct effect on production deviance when emotional intelligence was low, but not when high.Originality/valueThe study is the first to examine the relationship between perceived threat of terrorism and production deviance. Moreover, no study to date has examined the mediating role of emotional exhaustion between perceived threat of terrorism and production deviance. Finally, up till now, it is unknown that emotional intelligence moderates the relationship of perceived threat of terrorism with emotional exhaustion and production deviance.