This study aims to elaborate on how work-life balance practices influence organizational cynicism through the mediation effects of person-job fit. We collected data from 331 nurses through a self-administered survey, and we tested our hypothesized model through partial least square structural equation modeling techniques using SmartPLS software. The findings revealed that WLB practices influenced OC negatively and PJF positively. We further found that PJF negatively influenced OC and mediated WLB practices’ effect on OC. These findings imply that nurses should be (...) provided WLB practices to meet their job and home responsibilities and thus have a less cynical attitude toward the organization. (shrink)

The COVID-19 pandemic has caused a global crisis that particularly hit employment globally. Due to the economic crisis, many small businesses attempted to minimise their expenses by either closing or downsizing. During such organisational situations, the employees face negative workplace attitudes that lead to knowledge hiding and affect team performance. This study examines negative attitudes and their effect on team performance. Further, this study examines the mediating effect of knowledge hiding and moderating the role of servant leadership. Through a multi-time (...) data collection approach, the authors obtained 363 responses from the education sector in China during the COVID-19 pandemic. PROCESS Hayes model 1 and 4 were used for mediation and moderation analysis. Results show that job insecurity, cynicism, and role stress are significant forces behind knowledge-hiding behaviour. Furthermore, the knowledge hiding behaviour adversely affects task performance. Servant leadership shows a buffering effect on knowledge hiding behaviour caused by negative workplace attitudes. This is one of the first studies in the South Asian environment to examine the association between employees’ negative attitudes and task performance using knowledge hiding as a mediator and servant leadership as a moderator in the COVID-19 scenario. Lastly, the paper concludes with a consideration of its theoretical, practical implication and future direction. (shrink)

Though the current research stream has provided some risk factors for envy at the workplace, little is still known about the drivers and consequences of envy. Based on Vecchio’s theory, this study investigates the ripple effect of the span of supervision on envy. Moreover, it sheds light on the moderating role of meaningful work in their relationship. The data comprising sample size 439 were collected from confrères of four fast food companies listed on the Stock Exchange of Pakistan. Partial Least (...) Square Structural Equation Modeling technique was implemented through SmartPLS 3.3.2 to analyze the measurement and structural relationships. The results demonstrate that a narrow span of supervision will increase work engagement, and reduce instigated incivility via decreasing envy and resource depletion in sequence. Moreover, meaningful work would help regulate the inimical stream of dénouement of envy. Theoretical and practical implications, along with the limitations and future directions, have also been discussed. (shrink)

Energy poverty is a problem that affects developed and developing economies, and its mitigation is of great significance to social welfare. EP affects Latin American countries, and policymakers have recently attempted to address this issue, particularly in the aftermath of the recent economic crisis. It is essential to measure and evaluate EP to implement strategies and policies effectively. Using a panel quantile regression approach, we investigate the heterogeneous impact of green finance, renewable energy, and energy efficiency on EP for 33 (...) Latin American countries from 2000 to 2018. Furthermore, certain associated control variables are incorporated into our model to avoid an omitted variable bias. According to empirical results, the impact of independent variables on EP is heterogeneous. Specifically, green finance is an essential source of alleviating EP, and it has a significant positive effect across all quantiles, but it is especially strong in the middle quantiles. RE and EE significantly mitigate EP, with the strongest effects occurring at higher quantiles. By including green finance, RE, and EE as the main explanatory determinants of EP, the findings urge policymakers in Latin American countries to design a comprehensive energy conservation policy to minimize the effects of massive EP. (shrink)

BackgroundIn recent years, technological advancements have increased the importance of innovation activities. Therefore, firms invest millions of dollars in innovation activities to ensure long-term business sustainability. Similarly, consumer concerns have increased dramatically over the past years. Thus, brand loyalty has become a top priority for firms and consumers. In this background, this research examines how firms’ innovation activities translate into consumer brand loyalty to assure business sustainability in Asian markets, particularly China, Pakistan, and Indonesia.ObjectivesThis study’s specific objectives are to comprehend (...) the concept of firms’ innovation activities and their effect on the brand prototype. Examine the effect of the brand prototype on global brand preference, recommendation, and loyalty among Asian consumers. Find out the impact of brand preference on brand recommendations and the influence of brand recommendations on brand loyalty among Asian consumers.Materials and methodsA total of 814 consumers from Asian countries participated in this study, and structural equation modeling was used to analyze the data.ResultsThe findings indicate that firms’ innovation activities, such as processes, products, and store environment, positively influenced the brand prototype, thereby increasing consumer brand knowledge. Likewise, brand prototype contributes to developing brand preference, brand recommendation, and brand loyalty among Asian consumers. Lastly, consumer brand preference significantly influenced brand recommendation, which positively improves consumer brand loyalty in Asia.ConclusionThis study concluded that Asian consumers have favorable perceptions of firms’ innovation activities, which influences their ability to develop brand prototypes to increase consumer brand knowledge. Similarly, brand prototype fosters brand preference, recommendation, and loyalty. Likewise, favorable brand preference encourages consumers to recommend the brand to others, strengthening brand loyalty. Thus, firms should invest in innovation activities to strengthen consumer brand loyalty in Asian markets. Consequently, this study may assist multinational corporations in increasing their business volumes and market shares in Asia.Managerial recommendationsThis study provides important managerial recommendations. The findings revealed that global managers can develop and implement several branding strategies for sustaining their businesses in the Asian environment. (shrink)

While major religions espouse moral values encouraging prosocial behavior, the empirical evidence supporting the effectiveness of religious influence on such behavior, as proposed by the religious pro-sociality hypothesis, remains inconclusive. To explore this further, we conducted two studies to test this hypothesis in Pakistan, a Muslim-majority Asian nation, focusing on whistleblowing as a prosocial behavior. The first study gathered cross-sectional data from 323 undergraduate business students in Karachi, Pakistan, utilizing hypothetical scenarios of academic cheating and bank embezzlement. Participants completed a (...) scenario-based questionnaire assessing intrinsic religiosity, personality traits, and whistleblowing intentions. Measures were adapted for the Muslim context, with intrinsic religiosity assessed using the Age Universal Intrinsic-Extrinsic (AUIE) scale and personality traits measured using the Ten-Item Personality Inventory (TIPI) scale. Regression analysis of these data revealed that while intrinsic religiosity significantly predicted whistleblowing intentions in the academic cheating scenario, it did not do so in the bank embezzlement scenario. Furthermore, multiple regression modeling to test moderating effects of personality traits did not yield significant results for either scenario. The second study employed an experimental design to observe actual whistleblowing behavior among 85 undergraduate business students in Karachi, Pakistan. Participants were randomly assigned to either a religious or a neutral condition, aiming to assess the impact of intrinsic religiosity on whistleblowing behavior. The experiment used a cover story which involved a confederate cheating during an intelligence quotient (IQ) test. The purpose of this design was to examine whether the participant, acting as the sole witness to wrongdoing, would intervene and blow the whistle. Data analysis using logistic regression indicated that intrinsic religiosity did not significantly predict whistleblowing behavior across both the experimental and control conditions. These contrasting results highlight the complexity of whistleblowing, emphasizing its subjective nature and the influence of social dynamics on behavior. (shrink)

This study aims to examine the underlying mechanism of the relationship between perceived green human resource management and perceived employee green behavior. By drawing on attitude and social exchange theories, we examined green commitment as a mediator and green knowledge sharing as a moderator of the GHRM–EGB relationship. The study employs partial least square structural equation modeling to analyze 329 responses. Data were collected in two time lags. The empirical results confirmed that GC mediates the relationship between GHRM and EGB. (...) However, the study results found that GKS moderated the indirect influence of GHRM on green behavior via GC. This research signifies the effect of GHRM, GKS, GC, and green behavior on organizations’ sustainability and environmental management. Despite the emerging literature on the significance of green practices in organizations for environmental management, no study has examined the moderating role of GKS on the indirect effect of GHRM on green behavior via mediating role of GC. This study offers valuable insight into environmental management in organizations through green practices and green behavior. (shrink)

Social interactions through social commerce platforms empower consumers to share their personal experiences with others, but its role becomes more significant for societal protection during COVID-19. Numerous scholars have studied e-commerce extensively, but there is a lack of studies to identify social commerce characteristics to attract potential consumers during COVID-19. This study aims to examine the role of social commerce constructs by integrating social presence as a moderator in the model to explain consumers online shopping intentions in a Pakistani context, (...) where lack of trust on the reliability and validity of comments from other consumers being considered the growing concern toward the success of social commerce. The quantitative data were collected from the respondents living in different cities of Pakistan. Most of the hypothesis supported and demonstrate the positive response from the Pakistani consumers having experience in shopping through social commerce platforms. The findings of this study will help scholars and managers to understand the attitude of Pakistani consumers. (shrink)

Drawing on social cognitive theory and social information processing theory, this study investigated how organizations' efforts to embody environmental corporate social responsibility (ECSR) shape consumer perception of a green corporate image through employees' environmental passion and pro-environmental behavior (PEB). To test our hypotheses, we collected multisource time-lagged data from 214 employee–customer dyads from hotel and banking sector organizations in Pakistan. The findings show that organizations' green corporate image is a function of their efforts to engage in ECSR activities as demonstrated (...) through employees' environmental passion and PEB. These findings have important implications in the environment and management domains because it can help organizations draft useful strategies to counter environmental degradation and generate a green corporate image in customers' minds through employees' green behavior. (shrink)

Since the outbreak of COVID-19, reaction quarantine, social distancing, and economic crises have posed a greater risk to physical and psychological health. Such derogatory mental health stigma is associated with adverse outcomes in the student population. The purpose of the current study is to provide a timely evaluation of the COVID-19 pandemic and its adverse effects on students’ psychological well-being to sustain economic sustainability. A thorough review of the literature and current studies, significant emphasis of socio-demographic indicators, interpretation of physical (...) symptoms, home quarantine activities, and COVID-19 unique stressors were extracted. Data were collected through electronic surveys from 640 university students at local and foreign universities. The findings revealed substantial adverse effects resulting in varying levels of stress, symptoms of depression, and specific discomfort in the case. Among COVID-19 stressors, financial instability, unpredictability toward future/career, and media exposure have been described as common factors that cause poor psychological well-being and weaken economic sustainability. COVID-19, quarantine, self-isolation, and onerous interventions primarily weaken university students’ mental health. The emphasis on this vulnerable category, however, is substantially absent from the literature. This research addresses the urgent need to develop possible solutions and preventive measures to promote economic sustainability by ensuring students’ psychological well-being. (shrink)

Nature-inspired optimization techniques are useful tools in electrical engineering problems to minimize or maximize an objective function. In this paper, we use the firefly algorithm to improve the optimal solution for the problem of directional overcurrent relays (DOCRs). It is a complex and highly nonlinear constrained optimization problem. In this problem, we have two types of design variables, which are variables for plug settings (PSs) and the time dial settings (TDSs) for each relay in the circuit. The objective function is (...) to minimize the total operating time of all the basic relays to avoid unnecessary delays. We have considered four models in this paper which are IEEE (3-bus, 4-bus, 6-bus, and 8-bus) models. From the numerical results, it is obvious that the firefly algorithm with certain parameter settings performs better than the other state-of-the-art algorithms. (shrink)

Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election predictions. Objective. Identify, categorize, and present a comprehensive overview of the approaches, techniques, and tools used in election predictions on Twitter. Method. Conducted a systematic mapping study on election predictions on Twitter and provided empirical evidence for the work published between January 2010 and (...) January 2021. Results. This research identified 787 studies related to election predictions on Twitter. 98 primary studies were selected after defining and implementing several inclusion/exclusion criteria. The results show that most of the studies implemented sentiment analysis followed by volume-based and social network analysis approaches. The majority of the studies employed supervised learning techniques, subsequently, lexicon-based approach SA, volume-based, and unsupervised learning. Besides this, 18 types of dictionaries were identified. Elections of 28 countries were analyzed, mainly USA and Indian elections. Furthermore, the results revealed that 50% of the primary studies used English tweets. The demographic data showed that academic organizations and conference venues are the most active. Conclusion. The evolution of the work published in the past 11 years shows that most of the studies employed SA. The implementation of SNA techniques is lower as compared to SA. Appropriate political labelled datasets are not available, especially in languages other than English. Deep learning needs to be employed in this domain to get better predictions. (shrink)

_Unemployment poses a significant threat to Pakistan's economy alongside other global countries. The current study tries to determine the substantial determinants affecting unemployment in the country. Data was retrieved from the worldwide development indicator (WDI) and worldwide governance indicators (WGI) by employing Time series analysis from 1996 to 2021. Augmented Dicky Fuller and Philips-Perron Unit root test were employed to check the stationary of the data. To figure out the short-run and long-run cointegration among variables, the model Autoregressive distributed lag (...) (ARDL) was applied. Findings indicate that all variables were statistically significant. Inflation, FDI and GDP are negatively affecting unemployment. While population growth, external debt and governance index have a positive association with unemployment. Growing population and external debt are substantial contributors to unemployment, while governance reveals inadequate effectiveness in addressing this challenge. Study recommended to improve FDI and GDP growth in Pakistan to reduce unemployment. Furthermore, govt stability and effective policies are necessary to overcome the problem of unemployment._. (shrink)

Social media marketing has become one of the most significant growth paths for many businesses in today’s world. However, many companies are still unclear about using social media marketing to get their advantages, particularly in an e-commerce environment. In this background, this study is proposed to examine the effects of social media marketing activities on relationship quality, such as commitment, trust, and satisfaction in order to predict consumers’ online repurchase intentions in China’s e-commerce environment. This study proposed a theoretical model (...) by using the stimulus-organism-response theory. Using a structured questionnaire and purposive sampling, this study examined the responses of 403 consumers through partial least square-structural equation modeling. The findings discovered that SMMAs significantly strengthen the relationship quality factors, such as commitment, trust, and satisfaction, which in turn positively increase consumer online repurchase intentions in China’s e-commerce industry. This is novel research that contributes to the S-O-R theory and provides several managerial guidelines that assist managers in improving their business performance in the e-commerce industry. This research also highlighted some limitations. (shrink)

Built on the integrated theoretical framework of antecedents of flow and expectation confirmation model, this research investigates the way flow experience drives the online students’ intention to engage in online English teaching platforms. This study focused on the online students engaged in online English learning platforms in Taiwan. A total of 500 online students were selected. An online survey was conducted with the help of a marketing research agency located in Taiwan. According to the results, the online students’ flow experience (...) was found to be in a significant relationship with continuous intention. The antecedents, including perceived enjoyment, challenge, and situational involvement, were found to be in a positive relationship with flow experience; however, confirmation and perceived vividness did not have significant effects on the flow. Furthermore, flow and confirmation were found to be in a significant relationship with perceived usefulness and satisfaction. Moreover, perceived usefulness was found to be in a significant relationship with satisfaction and continuous intention. Lastly, satisfaction was found to be in a significant relationship with continuous intention. Finally, the questions proposed in this research with their empirical findings offer profound understanding for establishing a well-devised online English learning platform that can motivate online learning. These results and managerial implications for online English language platforms are innovative and significant in practice. (shrink)

Using a time-lagged design, we tested the main effects of Islamic Work Ethic (IWE) and perceived organizational justice on turnover intentions, job satisfaction, and job involvement. We also investigated the moderating influence of IWE in justice–outcomes relationship. Analyses using data collected from 182 employees revealed that IWE was positively related to satisfaction and involvement and negatively related to turnover intentions. Distributive fairness was negatively related to turnover intentions, whereas procedural justice was positively related to satisfaction. In addition, procedural justice was (...) positively related to involvement and satisfaction for individuals high on IWE however it was negatively related to both outcomes for individuals low on IWE. For low IWE, procedural justice was positively related to turnover intentions, however it was negatively related to turnover intentions for high IWE. In contrast, distributive justice was negatively related to turnover intentions for low IWE and it was positively related to turnover intentions for high IWE. (shrink)

The current study investigates whether tournament incentives motivate chief executive officer to be socially responsible. Furthermore, it explores the role of sub-national institutional contingencies [i.e., state-owned enterprises vs. non-SOEs, foreign-owned entities vs. non-FOEs, cross-listed vs. non-cross-listed, developed region] in CEO tournament incentives and the corporate social responsibility performance relationship. Data were collected from all A-shared companies listed in the stock exchanges of China from 2014 to 2019. The study uses the baseline methodology of ordinary least squares and cluster OLS regression. (...) Moreover, firm-fixed effects regression, two-stage least squares regression, and propensity score matching deal with the endogeneity problem and check the robustness of the results. The results provide reliable evidence that tournament incentives motivate CEOs to be more socially responsible. On the other hand, sub-national institutional contingencies positively affect the association between CEO tournament incentives and CSRP. The findings have important implications for companies and regulators who wish to enhance CSP by providing incentives to top managers. (shrink)

The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking over most of the research conducted in this field, especially in the biomedical domain. Unlike other languages, Arabic suffers from lack of resources. This work presents a BERT-based (...) model to identify biomedical named entities in the Arabic text data that investigates the effectiveness of pretraining a monolingual BERT model with a small-scale biomedical dataset on enhancing the model understanding of Arabic biomedical text. The model performance was compared with two state-of-the-art models, and it outperformed both models with 85% F1-score. (shrink)

Synthesizing theories of ethical leadership, psychological climate, pro-environmental behavior, and gender, first, we proposed and tested a model linking supervisors’ ethical leadership and organizational environmental citizenship behavior via green psychological climate. Then we tested the moderating effect of gender on the indirect (via green psychological environment) relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Time-lagged (three waves, two months apart) survey data were collected from 447 employees in various manufacturing and service sector firms operating in China. Data were (...) analyzed using structural equation modeling, bootstrapping, and multi-group technique to test the hypothesized relationships. The results showed a positive relationship between employee ratings of supervisors’ ethical leadership and organizational environmental citizenship behavior. Moreover, green psychological climate mediates the relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Importantly, the multi-group analysis revealed that gender moderates the indirect relationship (via green psychological climate) between supervisors’ ethical leadership and organizational environmental citizenship behavior. The study carries useful practical implications for policymakers and managers concerned about environmental sustainability. (shrink)

Authentic leadership has appeared as a significant field of research. Building on social exchange theory that explicates how individuals mutually mechanize reciprocation and eventually establish a trust-based relationship, we postulated a positive relationship between authentic leadership and followers' organizational citizenship behaviors (OCB). Based on a two-wave time-lagged design, the data were obtained from 270 employees working in the private banking sector of Pakistan. We found that authentic leadership is positively associated with subordinate’s OCB, as well as, leads to a higher (...) level of both affective and cognitive-based followers' trust. The results also indicated that both affective and cognitive-based trust positively mediated the relationship between authentic leadership and OCB. The implication for theory and practice are discussed. (shrink)

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' CL. This study addresses the key (...) concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions. (shrink)

This study develops a conceptual framework and investigates green human resource practices —green recruitment and selection, green training and development, and green reward and compensation? effects on pro-environmental psychological climate and pro-environmental behavior, which cause green corporate social responsibility. We employ information technology capabilities as a moderator between the GHRM and pro-environmental behavior. It applies a convenience sampling technique and survey questionnaire to collect data from 388 employees at CPEC projects. Results demonstrate that GHRM positively influences pro-environmental psychological climate and (...) pro-environmental behavior that significantly develops GCSR. IT capabilities significantly moderate the relationships between GHRM and pro-environmental behavior. The study findings add to the body of green HRM practices, strategic management, and information processing and policy makers better postulate, align, and exercise their green HRM practices for its synergetic effects for green CSR and sustainability. We also acknowledge some limitations and provide future directions. (shrink)

Our objective is to examine the effects of Big Five personality traits on ethical ideologies using a time-lagged design of 406 employees of higher education institutions in Pakistan. Based on low/high idealism versus relativism, we investigate the conceptual linkage between each of the personality traits and moral philosophy. The results illustrate that extraversion and openness to experience believed on subjectivism moral philosophy, agreeableness believed on situationism, and neuroticism believed on absolutism moral philosophies. In addition, contentiousness believed on exceptionism moral philosophy. (...) Furthermore, managerial implications and future research directions are suggested. (shrink)

We examined a largely ignored but imperative dimension of safety literature by testing the impact of ethical leadership style on organizational safety performance. We also tested dual mediating paths of safety culture and safety consciousness in the relationship between ethical leadership style and organizational safety consciousness. Data were collected from a large public sector telecom company in Pakistan. Confirmatory factor analysis was used to assess the reliability and validity of the study scales and model fit. Preacher and Hayes’s macro of (...) mediation was employed to test the direct and indirect paths proposed in the study. The findings suggest that ethical leadership has a positive impact on organizational safety performance. Partial mediating roles of safety culture and safety consciousness were also found between the dependent and independent variables. Theoretical and practical implications are discussed. (shrink)

Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to as the diagnostic assistant tool for screening of cardiac disorder. The research purposes of a cardiac disorder detection system from 12-lead-based ECG Images. The healthcare institutes used various ECG equipment that present results in nonuniform formats of ECG images. The research study proposes a generalized methodology to process all formats of (...) ECG. Single Shoot Detection MobileNet v2-based Deep Neural Network architecture was used to detect cardiovascular disease detection. The study focused on detecting the four major cardiac abnormalities with 98% accuracy results were calculated. The work is relatively rare based on their dataset; a collection of 11,148 standard 12-lead-based ECG images used in this study were manually collected from health care institutes and annotated by the domain experts. The study achieved high accuracy results to differentiate and detect four major cardiac abnormalities. Several cardiologists manually verified the proposed system’s accuracy result and recommended that the proposed system can be used to screen for a cardiac disorder. (shrink)

Generally toxic employees are under performers, yet some get better salaries and excel at workplace, getting positioned at higher ranks. This research assesses the relationship between the dark triad (Narcissism, Machiavellianism, and Psychopathy) and perceived victimization with a focus on the mediating effect of abusive supervision and the moderating effect of mindfulness. The data were gathered in three waves. Both the structural equation model with partial least square and Process were used to analyze the data. The study findings suggest that (...) abusive supervision plays a mediating role in the association between the dark triad and perceived victimization. However, the results did not support the mediating role of abusive supervision in the association between narcissism and perceived victimization. Moreover, the findings suggest that mindfulness weakens the effect of abusive supervision on perceived victimization. Furthermore, our findings support the mediated-moderation model. Theoretical and practical implications of the results are also discussed. (shrink)

This study sheds light on strategies for retaining skilled pharmacists in Pakistan's pharmaceutical sector, offering valuable insights for both academia and industry stakeholders by investigating the impact of human resource management practices, including training and development, compensation and rewards, job performance, and job satisfaction, on employee retention. It also examines the moderating role of career growth in this context. Theoretical foundations are grounded in international migration theories and social exchange theory, providing a comprehensive framework for the study. A cross-sectional survey (...) design was used to collect data from 254 pharmacists in southern Punjab, Pakistan. Structural equation modeling (SEM) was employed for data analysis. Findings reveal that training and development, compensation and rewards, job performance, and job satisfaction all have significant direct effects on employee retention. Additionally, career growth acts as a crucial moderator, strengthening the relationship between training and development and job performance, as well as compensation and rewards and job satisfaction in relation to employee retention. Theoretical implications emphasize the importance of tailored training programs, fair compensation practices, and career growth opportunities. Practical recommendations include creating a positive work environment, rewarding high-performing employees, and fostering career development. Future research directions encompass longitudinal studies, the influence of organizational culture and technology, regional variations, and additional factors affecting retention. (shrink)

The purpose of this research is to highlight the relationship between green product attributes and consumer trust that influence consumers’ decision to purchase green products in the context of Pakistan. This study contributes to determining quantitatively how green product attributes such as physical, perceptual, and reflexive attributes influence consumers’ trust to purchase a green product and investigates the mediating role of green marketing. Data was collected from different industrial sectors through a survey questionnaire. We employed Structural Equation Modeling using the (...) SMART-PLS software to check the reliability and validity of the constructs, and to test the hypotheses. This study reveals variations in terms of shaping the sustainable consumers’ buying behavior by modifying product attributes and green marketing strategies that are in congruence with the proposed hypotheses of this study. In the end, the findings and interpretations of the results are given which can guide the managers to develop effective green marketing campaigns in reshaping the purchase intentions of consumers toward their green products. (shrink)

Healthcare workers in Pakistan are still fighting at the frontline to control the spread of severe acute respiratory syndrome coronavirus-2 and have been identified as the earliest beneficiaries for COVID-19 vaccination by the health authorities of the country. Besides, the high vaccination rates of frontline healthcare workers are essential to overcome the ongoing pandemic and reduce the vaccines hesitancy among the general population. The current research employed the theory of planned behavior to investigate the COVID-19 vaccination behavior among FHWs in (...) Pakistan as well as the predictors of such behavior. Following the epidemic control and prevention policies, a sample of 680 FHWs were accessed to fill in the questionnaire evaluating the components of the TPB. Moreover, the potential role of anticipated regret and perceived susceptibility on COVID-19 vaccination behavior was also assessed. The partial least square structural equation modeling results revealed that the TPB components, as well as the AR, have positive associations with the COVID-19 vaccination behavior. The results further confirmed that PS positively affects the anticipated regret, attitude, and subjective norm to vaccinate against SARS-CoV-2. The perceived susceptibility also has a positive association with COVID-19 vaccination behavior through the mediation of anticipated regret, ATT, and SN. Our findings highlighted the importance of COVID-19 vaccination among healthcare workers, which can be applied to reduce vaccine hesitancy among the general public. (shrink)

This research explores the effect of servant leadership on prosocial rule-breaking (PSRB) and the mediating mechanism of public service motivation (PSM) between the association of servant leadership and PSRB. The said phenomenon is examined in the civil service context of Pakistan during the continuing crises of the COVID-19 pandemic, a situation where the traditional civil service policy and rule system has become highly complicated for passionate employees’ service performance and efficiency, and where servant leadership has received greater attention for inspiring (...) the attitudinal and behavioral outcomes of frontline workers during the pandemic. Data were collected from 546 frontline workers of the corona relief tiger force. The findings of the study revealed that servant leadership has a significant effect on PSRB and PSM, and that PSM significantly promotes PSRB. The results also revealed that servant leadership has a significant impact on PSRBviaengendering PSM. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

This paper analyzes the impact of the COVID-19 pandemic on the mental health of the teachers, specifically the techno stress arising in them as a result of issues faced by them in the use of technology when they conduct the online academic activities. It aims to assess the major factors related to the online teaching that specifically adds to techno stress on the teachers during the COVID-19 outbreak. Finally, the study aims to provide suggestions to the policymakers and the management (...) of the universities so that the effect of the COVID-19's on teachers' mental health and the related techno stress can be reduced. This paper is a literature review of the articles on the notion of techno stress on teachers and their mental health by searching the related articles with these terminologies using the renowned search engines of Google Scholar and Web of Science. A combination of the terms such as Coronavirus, COVID-19, mental health, psychological distress, techno stress, and online teaching were used in the article search for the review. The literature has suggested that the COVID-19 outbreak has significantly affected the mental health of the employees in general and specifically, the teachers who are engaged in online academic activities and teaching in the universities. The paper has identified a few factors that are the cause of the techno stress and provides recommendations for the university management and the policy makers for minimizing their negative impact on the teachers, in terms of the techno stress and their mental health. Coronavirus is a new strain of the viruses that has badly engulfed the entire population of the world. It is even now badly rising and causing deaths while this article is in the writing phase. The article has addressed the mental health concerns of the university teachers as they are now working from home using ICT for delivering the lectures and conducting the online teaching and learning activities for the students at their universities. This is a matter of grave importance now and requires immediate attention. Hence, this article broadens the scope of the research on the corona virus and its impact on the university teachers. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

Brain-computer interface multi-modal fusion has the potential to generate multiple commands in a highly reliable manner by alleviating the drawbacks associated with single modality. In the present work, a hybrid EEG-fNIRS BCI system—achieved through a fusion of concurrently recorded electroencephalography and functional near-infrared spectroscopy signals—is used to overcome the limitations of uni-modality and to achieve higher tasks classification. Although the hybrid approach enhances the performance of the system, the improvements are still modest due to the lack of availability of computational (...) approaches to fuse the two modalities. To overcome this, a novel approach is proposed using Multi-resolution singular value decomposition to achieve system- and feature-based fusion. The two approaches based up different features set are compared using the KNN and Tree classifiers. The results obtained through multiple datasets show that the proposed approach can effectively fuse both modalities with improvement in the classification accuracy. (shrink)

This study explores the impact of CEO ability on corporate environmental sustainability information disclosure. We take samples from Chinese A-share listed companies from 2010 to 2019 and use the ordinary least squares as a baseline regression model to check the relationship between CEO ability and corporate environmental sustainability information disclosure. Our findings are robust to different corporate environmental sustainability information disclosure measures and CEO ability. We found a positive association between CEO ability and corporate environmental sustainability information disclosure; thus, firms (...) with a more able CEO are more likely to disclose more corporate environmental sustainability information. Our results also found a significant negative interaction coefficient between CEO ability and CEO career concerns. As the CEO grows older, his/her ability decreases; therefore, corporate environmental sustainability information disclosure reduces. Furthermore, we document that a female CEO strengthens the relationship between CEO ability and corporate environmental sustainability information disclosure. The study results are important for understanding corporate environmental responsibility development and implementation, particularly in China. (shrink)

Half a million species of plants could be existing in the world. Classification of plants based on leaf features is a critical job as feature extraction from binary images of leaves may result in duplicate identification. However, leaves are an effective means of differentiating plant species because of their unique characteristics like area, diameter, perimeter, circularity, aspect ratio, solidity, eccentricity, and narrow factor. This paper presents the extraction of plant leaf gas alongside other features from the camera images or a (...) dataset of images by applying a convolutional neural network. The extraction of leaf gas enables identification of the actual level of chlorophyll and nitrogen which may help to interpret future predictions. Our contribution includes the study of texture and geometric features, analyzing ratio of Ch and N in both healthy and dead leaves, and the study of color-based methods via CNN. Several steps are included to obtain the results: image preprocessing, testing, training, enhancement, segmentation, feature extraction, and aggregation of results. A vital contrast of the results can be seen by considering the kind of image, whether a healthy or dead leaf. (shrink)

Current development in a deep neural network has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real-time performance. There are many deep learning-based techniques that have been proposed for the holographic image reconstruction, but these deep learning-based methods can still lack in performance, time complexity, accuracy, and real-time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network (...) holography framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel-based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer-generated holograms. The experimental results have demonstrated that the proposed method outperforms the existing methods. (shrink)

Jensen’s inequality is one of the fundamental inequalities which has several applications in almost every field of science. In 2003, Mercer gave a variant of Jensen’s inequality which is known as Jensen–Mercer’s inequality. The purpose of this article is to propose new bounds for Csiszár and related divergences by means of Jensen–Mercer’s inequality. Also, we investigate several new bounds for Zipf–Mandelbrot entropy. The idea of this article may further stimulate research on information theory with the help of Jensen–Mercer’s inequality.

In this paper, we utilized triangular conorms. The essence of using S-norm is that the similarity order does not change using different norms. In fact, we are investigating for a new conception for calculating the similarity of two Fermatean fuzzy sets. For this purpose, utilizing an S-norm, we first present a formula for calculating the similarity of two Fermatean fuzzy values, so that they are truthful in similarity properties. Following that, we generalize a formula for calculating the similarity of the (...) two Fermatean fuzzy sets which prove truthful in similarity conditions. Finally, various numerical examples have been presented to elaborate this method. (shrink)

Caricatures can help to understand the perception of a face. The prominent facial feature of a subject can be exaggerated, so the subject can be easily identified by humans. Recently, significant progress has been made to face detection and recognition from images. However, the matching of caricature with photographs is a difficult task. This is due to exaggerated features, representation of modalities, and different styles adopted by artists. This study proposed a cross-domain qualitative feature-based approach to match caricature with a (...) mugshot. The proposed approach uses Haar-like features for the detection of the face and other facial attributes. A point distribution measure is used to locate the exaggerated features. Furthermore, the ratio between different facial features was computed using different vertical and horizontal distances. These ratios were used to calculate the difference vector which is used as input to different machine and deep learning models. In order to attain better performance, stratified k-fold cross-validation with hyperparameter tuning is used. Convolution neural network-based implementation outperformed the machine learning-based models. (shrink)

Landslide is a critical natural geological hazard that causes severe damage to property, infrastructure, and humans. In general, some location-specific factors trigger a landslide. Wireless sensor network is an enabling technology to monitor most of the parameters associated with these factors. A challenge in landslide monitoring through WSN is that each sensed data item might be critical whereas the underlying wireless communication is often unreliable. In case of landslides, the terrains have irregular shapes, providing harsh conditions for wireless communication thereby (...) more data loss may be expected. This study focuses on the effect of lossy communication in WSN on the efficiency and accuracy of landslide monitoring systems. To this end, collaborative local data analysis is used to enable each node to decide locally whether its sensed data corresponds to a potential event-of-interest. Through extensive simulations, the performance of various landslide prediction and detection models has been evaluated. By and large, the study lets a significant insight into landslide monitoring before implementing a parameterized application for real-world deployment. (shrink)

Business Ethics, the Environment & Responsibility, EarlyView.

Online forums have become the main source of knowledge over the Internet as data are constantly flooded into them. In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high-quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from (...) discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets. (shrink)