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The paper aims to explore the problems related to the financial management of municipal corporations in India and to suggest solutions.

The study is based on primary data collected from a sample of 577 employees of municipal corporations working in four metro cities of India, namely Chennai, Mumbai, Kolkata, and Delhi. Data were put through exploratory and confirmatory factor analysis for problem identification and inferences were classified and grouped to map the solutions for these problems.

The study found that municipal corporations in India face four major problems or issues in their financial management. These problems are mainly related to the four dimensions: Power, Interruptions, Finances, and Resources. The model used to explore these four types of issues is named as “PIFR model” by the author.

The findings suggest that real-world problems can be represented through a conceptual model that helps in identifying practical suggestions which can be implemented by municipal corporations at the ground level for better financial management.

This study aims to measure the impact of loneliness, physical activity (PA) and self-esteem on the health of retired people and also checks the moderating role of living arrangements and gender of the elderly people on this relationship.

Four standardized scales were used in the study to measure four different constructs: Self-Worth Questionnaire, UCLA Loneliness Scale Version 3, General Health Questionnaire-28 and Physical Activity Scale for Elders. Structural equation modelling was applied to the four constructs.

The study concluded that loneliness has a negative and significant impact on the health of retired people, while self-esteem and PA have a positive and significant impact on their health.

The study is among the few to include multiple instruments to measure abstract parameters in the field of health care. The paper brings out implications not just for academicians but also for policymakers, considering the complex situation prevailing in the emerging economy.

This paper aims to identify the dimensions of the political empowerment of Indian women and assess the factors responsible for the lacunas that hold women back in their potential.

The research was based on primary data collected through a personal interview method from a sample of 68 women managers working in five different sectors of the Indian economy, namely; IT, education, telecom, banking, and hospitality sector. Further, data on the five factors from a sample of 423 women employees from the above-mentioned sectors have been collected and analyzed using a multiple regression model with control variables (marital status and generation gap).

The major factors churned out that are needed for the political empowerment of women are namely, information or awareness, family support or family environment, legal environment, political environment, and personal ambitions or internal motivation.

The present study has presented new insight into the field of women and politics by providing a case study into the dimensions of political empowerment among Indian women. The pilot model developed in this study can be initiated and replicated across the land on being successful.

This paper aims to probe into the linkages between the corporate social responsibility (CSR) practices of banks and the cross-buying intentions of banking customers. Though the authors could not find any direct link between these two concepts on theoretical ground, but an effort has been made to identify the impact of CSR on cross-buying intentions through corporate reputation and relationship quality. Like other industries, the Indian banking industry has also witnessed a balance between its social-environmental responsibilities and its clearly defined economic responsibility to earn profit.

The universe for the present study constitutes the customers of the entire Indian banking industry. Considering the cost and time constraints, the study was limited to a sample of 347 public and private bank customers in the Rajasthan region based on the convenience sampling method. Data were collected using a structured questionnaire and analyzed through structural equation modeling. CSR measures included philanthropic and ethical responsibility.

Results revealed that corporate reputation and relationship quality both play a mediating role in the linkages between CSR and cross-buying intentions.

The study suggests integrating marketing strategy with its CSR strategies to encourage cross-buying intentions. While making the cross-selling agenda, they should bear reputation in mind because at the relationship development phase, customers generally rely on reputation than their evaluation of bank’s products for cross-buying.

This study is the first in marketing literature which relates the concept of CSR and the cross-buying.

This study analyzes the impact of exchange rate volatility (ERV) on inbound tourist arrivals from four ASEAN countries namely Indonesia, the Philippines, Singapore, and Thailand during 1970–2017. Volatility in the exchange rates between the tourist currency and ringgit Malaysia is measured using the Generalized Autoregressive Conditional Heteroskedasticity model. The results from Autoregressive Distributed Lagged models indicate that ERV has no significant impact on tourist arrivals from ASEAN to Malaysia. This implies that tourists from these countries may not be sensitive to ERV when choosing Malaysia as their travel destination. There are two possible explanations for the results. First, Malaysian ringgit has been depreciating against major currencies and regional currencies in recent years, which makes ringgit relatively cheaper than other ASEAN currencies. Second, the empirical results of the study support the argument that ERV has a more serious impact on tourist spending compared to tourist arrivals.

Over the last decade, customer experience management has gradually emerged as the most important activity for organisations. Organisations have turned towards leveraging the ubiquitous and easy-to-use technology in enhancing and enabling experience for the time-crunched customers of today who are looking for greater convenience and choices. It is therefore not surprising that disruptive technologies such as smartphones, virtual and augmented reality, cloud computing, big data analytics, Internet of things, artificial intelligence and robotics have also found their way into the design of customer experience. This chapter aims to present an overview of the technologies that have transformed the customer experience landscape. This chapter contributes by showcasing two illustrative cases from very diverse domains, a private sector bank and a public sector transportation organisation, to elucidate how India, a rapidly developing economy, is embracing technology to enhance the customer experience.

Adequate, reliable, and efficient urban infrastructure systems (UIS) are fundamental to sustainable development, social mobility, and economic vitality. As communities continuously rely on basic infrastructure services to support their daily communal functions, major components of UIS are subject to heavy use, and thus rapidly deteriorate over time; hence, it is critical that efficient infrastructure management strategies practices are in place. As current strategies remain confronted with various limitations including adaptability to changing conditions, lack of public engagement, and cost-effectiveness, this study explores social media data mining as an approach to revitalise and support current urban infrastructure monitoring strategies by extracting valuable insights from public opinion. Twitter messages or ‘Tweets’ pertaining to public infrastructure in The Philippines were collected and analysed to identify recurring issues in public infrastructure, emerging topics in public discussions, and the overall perception of the public on infrastructure services. This study presents a topic model that extracts dominant topics from aggregated social media data and a sentiment analysis model that determines public opinion sentiment in relation to different urban infrastructure components. The findings of this study highlight the potential of social media data mining to surpass the limits of conventional data collection techniques and the importance of public opinion as a key driver for a more user-involved decision-making in infrastructure management and as an important social aspect that can be utilised to support planning and response strategies in routine maintenance, preservation, and improvement of UIS.

The purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic. Within the context of this paper, adoption is largely referring to the factors that influence the acceptance and use of AI as a tool for personalized learning.

To develop our understanding and appreciation of the valuable impact that AI potentially has upon personalized learning the following systematic literature review was conducted. An acceptable systematic literature review is a comprehensive method of fully analysing and evaluating all available research in the chosen area or specific research query.

The findings from this study have particular implications for personalized learning in the adoption and diffusion of AI and an increasing integration of macro, structural, and micro, individual. Developing and managing AI in education is seen, from the literature, to becoming more embedded in the teaching and learning process. The paper identifies the following: antecedents that supports the adoption of AI for personalized learning; application of AI technologies in the teaching and learning process; AI technologies that enable personalized instruction and learning; generative AI that supports intuitive learning through tracking data.

Personalized learning remains focused on customizable “choice-driven” learning and education. In addition, personalized learning and instruction is defined as being a responsive and structured method that adapts to each individual learner’s method of learning so that all may achieve their capabilities and actively participate. This solidifies the intrinsic connection between teaching and learning through personalized technologies such as AI.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.