Search results

Corruption prevails in societies and systems, but it is because of the individuals and officials who practice it. It is individuals’ characteristics, attitudes, views and choices that spur them to act ethically or not. This study aims to investigate whether beliefs, values and behavior vary across countries in perspective of bribery and tax cheating.

This study used Order Logistic Regression on microlevel data from World Values Survey wave VI (2010–2014) for 58 countries to find factors of tax cheating and accepting bribes.

This study revealed some interesting findings while comparing upper-income countries and lower- and middle-income countries. Justifiability for accepting bribe is negatively affected by age, patriotism, interest in politics, university education while positively affected by employment and income. Justifiability for cheating on taxes is negatively affected by confidence in justice system, interest in politics and marital status while positively affected by income, patriotism, confidence in political parties and good health. This study finds some valuable insights to the policymakers to device policy to overcome financial corruption and its acceptability in the masses.

This paper fills the literature gap by adding a wide range of variables related to demography, socioeconomic status, trust on political, judicial and government institutes, well-being, patriotism and religiosity. Moreover, this paper compares the behaviors of a wide range of countries that include both developed and developing economies.

The soliton solutions are obtained by using extended rational sin/cos and sinh-cosh method. The methods are powerful and have ease of use. Applying wave transformation to the nonlinear partial differential equations (NLPDEs) and the considered equation turns into a nonlinear differential equation (NODE). According to the methods, the solution sets of the NODE are supposed to the form of the rational terms as sinh/cosh and sin/cos and the trial solutions are substituted into the NODE. Collecting the same power of the trigonometric functions, a set of algebraic equations is derived.

The main purpose of this paper is to obtain soliton solutions of the modified equal width (MEW) equation. MEW is a form of regularized-long-wave (RLW) equation that represents one-dimensional wave propagation in nonlinear media with dispersion processes. This is also used to simulate the undular bore in a long shallow water canal.

Thus, the solution of the main PDE is reduced to the solution of a set of algebraic equations. In this paper, the kink, singular and singular periodic solitons have been successfully obtained.

Illustrative plots of the solutions have been presented for physical interpretation of the obtained solutions. The methods are powerful and might be used to solve a broad class of differential equations in real-life problems.

To explore the role of digital leadership in fostering strategic agility, innovation adaptivity, organizational agility and resilience in the context of digital transformation.

Following an interpretive case study approach and using a thematic data analysis technique, we conducted 20 in-depth interviews with digital leaders from five different media firms across the UAE.

The findings reveal that digital leaders are central to developing and executing digital strategies that enhance organizational agility and competitive edge, particularly in firms’ digital transformation. Digital leaders catalyze innovation and adaptability, ensuring the organization’s readiness for technological and market shifts. Moreover, digital leaders are instrumental in fostering an environment that promotes continuous learning, technological integration and a culture of change, which drives organizational agility and resilience.

The originality of this study lies in its focused examination of digital leadership within the UAE’s media sector, offering new insights into how digital leadership drives strategic agility, innovation adaptivity, organizational agility and resilience in a regionally specific digital transformation context. Our findings contribute to the broader academic and practical understanding of digital transformation in the media industry.

This book is essential for anyone in artificial intelligence (AI) and destination management in the tourism industry or government. The book includes both theoretical and practical writings for stakeholders. In all chapters, we provide titles including AI, regenerative and green destinations, sustainable tourism, tourist motivations and expectations, good examples of smart destinations and regions, the regeneration of the tourism industry via AI, rethinking tourism activities and products, current issues in robots, self-service technology, effect of pandemic on smart destinations, sustainable gastronomy and regenerative tourism and tourism issues are discussed in the management plans of the centralisation. This book provides cases and empirical studies that deal in depth with the current situation, challenges, solutions and future strategies after technological development of tourism and increasing interest on smart destinations from a responsible perspective, for readers with an equitable interest or involvement with the organizations in inquiry.

This paper aims to examine the impact of general elections on the stock returns of the politically connected group affiliated firms of Pakistan.

This study uses the market model to assess the impact of political connections (PCs) on abnormal stock returns, before and after election events. We have used share price data of non-financial firms of Pakistan for the years 2008-2013.

It has been found that behavior of cumulative average abnormal returns (CAAR) is significantly different for standalone and politically connected group affiliated firms. The results reveal that CAARs of politically connected group affiliated firms have experienced less deviation as compared to stand alone firms. Therefore, it is argued that politically connected group firms may reduce the impact of political uncertainty on stock returns in comparison to stand alone firms.

This study is helpful for policy regulators of Pakistan to devise appropriate policies to maintain a level playing field for politically connected and standalone firms.

This study provides a new dimension to understand the role and association of PCs and general elections with stock markets returns.

This paper aims to describe the lived experiences of modern urban mothers in Pakistan as they navigate shared motherhood responsibilities with family elders. This paper brings to light their feelings, fears and ambitions towards safeguarding the environment for the future of their children, by reconciling ancient traditions of their female elders with contemporary sustainable consumption practices.

This phenomenological study explores lived experiences of urban mothers through in-depth personal interviews. Their discourse explores sharing childcare responsibilities with family matriarchs, negotiating “green” parenting strategies between intergenerational parenting partners.

Navigating life through the intersections of modernity and tradition and ethical choices and consumerism, urban mothers integrate wisdom of their ancestors into their modern lives to mitigate the environmental degradation of today.

This study sheds light on a unique genre of green mothers, termed as the traditionally green eco-mom, which allows modern mothers and their female elders to synchronously adopt sustainable childcare behaviours that overcome intergenerational barriers by reconciling contemporary lifestyles with traditional wisdom.

This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques.

This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data.

The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation.

This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences.

This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services.

This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

This paper purposed a multi-facet sentiment analysis system.

Hence, This paper uses multidomain resources to build a sentiment analysis system. The manual lexicon based features that are extracted from the resources are fed into a machine learning classifier to compare their performance afterward. The manual lexicon is replaced with a custom BOW to deal with its time consuming construction. To help the system run faster and make the model interpretable, this will be performed by employing different existing and custom approaches such as term occurrence, information gain, principal component analysis, semantic clustering, and POS tagging filters.

The proposed system featured by lexicon extraction automation and characteristics size optimization proved its efficiency when applied to multidomain and benchmark datasets by reaching 93.59% accuracy which makes it competitive to the state-of-the-art systems.

The construction of a custom BOW. Optimizing features based on existing and custom feature selection and clustering approaches.