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This chapter addresses the potential for knowledge, learning, and collaboration (KLC) cultures in public sector organizations. Public sector organizations are among the most complex for introducing or nourishing a KLC approach because there are multiple levels of cultures with varying levels of influence. We describe these complex cultures as tiers. First, we define public sector organizations’ business goals, purpose, and strategies. Then, the authors translate and interpret all five levels of culture for public sector organizations. The chapter also details the nature of cultural complexity, namely the four tiers of public sector cultures: (1) the company culture (Tier 1); (2) the public service culture (Tier 2); (3) the culture of the external environment (Tier 3); and (4) the internal KLC cultures (Tier 4). This chapter establishes a framework for describing an organization’s complex culture and determining the best KLC approach for the context.

According to Global Healthcare Security Index 2021, India ranked 66 out of 195 countries, indicating the need and scope for improvement. The Cooperative healthcare system which has been rendering exemplary services is yet to gain visible recognition in India. Given the need for upgrading the health infrastructure in India and providing more affordable health services to the country’s growing population, it would help appreciate the large role that cooperative healthcare can play along with others. This study explores the structure, conduct, and performance of healthcare co-operatives in India, the factors contributing to their success and failure, and the challenges they face. The Health Cooperatives have a strong presence in Kerala and Karnataka and are also coming up in other parts of the country. However, a detailed database of them for public awareness is very limited. The cooperative hospitals can meet the basic requirements of curative treatment in rural and poorly-endowed urban areas. The democratic way in which they function makes them a destination for a financially weaker section. They must retain this feature. The study covers two successful cases which reveal that India needs a more dense healthcare cooperative network. Since cooperative hospitals in tune with the spirit of service run on the principle of being ‘Not-for-Profit’ they need to be supported by the governments more liberally, without however interfering with their governance and administration.

Purpose: Thanks to the Fourth Industrial Revolution and the digital economy, digital banking has become an attractive business trend. Moreover, the spreading of the Covid-19 virus worldwide over the past two years has boosted the digitalisation of banking services. The development of digital banking is now becoming an uncontroversial issue that will attract the concern of scholars, bank managers, and policy-makers.

Methodology: As an emerging country with a young population having significant digital appliance joy, Vietnam will be a perfect case study to research the development of digital banking. Besides, digital banks, as well as the appliances of artificial intelligence (AI) in the banking sector, have appeared in Vietnam’s banking system at several different levels.

Findings: Moreover, most commercial banks in Vietnam are now in the race to complete their digital services to provide innovative digital banking services that add more value to their clients. Hence, the chapter will describe the overall picture of Vietnam’s current digital banking market.

Implications: Based on the crucial features of the operations of several digital banks and the appliances of AI in the digital banking sector in Vietnam during the chosen period, the author would like to give information on the potential of the Vietnamese digital banking market and suggest the key policies which the Vietnamese government should consider to support the digital transformation of the banking sector in Vietnam.

The Government of Eswatini (GoE) civil service wage bill has continued to rise in recent years. The personnel budget is still the largest single recurrent expenditure item in the budget in Eswatini. To control the civil service wage bill, the GoE introduced Lean Service Principle through Management Services Division (MSD). The civil service wage bill continues to rise despite the implementation of the Lean Service Principle. So far, there are no tangible outcomes that indicate that the principles applied have been effective in the reduction of the wage bill. Thus, this research aims to examine the question of why the Lean Service Principle failed to effectively slow the rampant growth of the civil service wage bill in the Kingdom of Eswatini. This study used the quantitative research approach to collect data on amounts spent on wages, the percentage increase of the wage bill for the period 2010–2017, and the percentage increase in the number of civil servants as per the Establishment Registers, 2010–2017. The study investigated the wage bill push factors, the shortcomings of the Lean Service Principle, and the Just-In-Time (JIT) Technique in the management and reduction of the GoE civil service wage bill. The study found the MSD has been applying the wrong methodologies in wage bill control, which has been evident in the continued yearly increase of the wage bill. The study recommends that the MSD should consider the utilisation of Human Resources Forecasting and Planning Techniques instead of using the Lean Service Principle and the JIT technique. This study will enable the Cabinet to make an appropriate decision on the mandate and future of the MSD, as there have been growing calls to disband the division due to the failure to reduce and/or control the wage bills as that is the core mandate of the division.

On the one hand, there is a long tradition of approaching management control and innovation as opposites that prompt organisational tensions. On the other hand, recent studies have shown that management control may foster innovation and promote innovative behaviour. At the same time, both these perspectives focus on innovation management, and discussions regarding the role of management control in innovation leadership are conspicuously absent from the literature. In this chapter, we analyse how innovation leaders use management control in two service companies. We demonstrate that, in contrast to innovation managers who employ management control systems primarily for planning, monitoring, and evaluation purposes, innovation leaders use management control for advocacy, engagement, and visibility.

Purpose: Different approaches have been applied to define and measure service quality as both a process and a performance-intensive presentation. The literature agreed that service quality assessments are essential in measuring performance, however they could only reach a partial consensus. Although the Servqual scale is the most widely known and used tool in measuring service quality, it has received various criticisms. This study presents the difficulties encountered in measuring service quality and an evaluation of the Servqual scale.

Methodology: The study provides a conceptual framework, examining the research on the subject in the literature and the criticisms of the Servqual scale. It is designed as a compilation/assessment to improve the perspectives of the interested parties by bringing together evaluations about the pros and cons of the most well-known service quality scale.

Findings: Measurement of service quality is a complex business. Although it has received various criticisms, the Servqual scale which enables the measurement of quality in the services sector is still the most frequently used measurement tool.

Practical Implications: The difficulty of defining the service and its quality, which arises from the characteristics of the services, does not eliminate the necessity of measuring the quality of the service. With this study, a conceptual framework has been provided on the subject, a collective evaluation has been made for the most widely used scale, and the ground has been prepared for improvement and development in the criticisms of the scale.

Companies are constantly striving for superior customer service that meets consumers' expectations. Products that do not provide consumers with good service quality are unlikely to meet the expectations of consumers. The aim is to maximize customer satisfaction and achieve financial success by closing gaps to provide high-quality service to consumers. Customers use quality of service to choose a service provider. This does not only include the quality of products or service but also the quality of customer service. The five essential elements (5Es) – experience, emotions, exclusivity, execution and engagement – must be used by companies to ensure that their products and services meet defined standards or customer's expectations. The customer's opinion of a service is formed immediately, regardless of whether it is positive or negative. The result of a negative customer experience is negative word of mouth, which would cause loss in business from dissatisfied customers as well as from potential customers who will no longer use the services. Using the gap model for service quality, this study proposes the essential 5Es of service quality. As a result of the synthesis of this current research, the company's service delivery will be improved by identifying weaknesses. The use of these 5Es for the control of service quality and monitoring of quality defects leads to better understanding and reduction of cost.

Purpose: The banking sector is facing a challenge in the quality of services rendered to the ultimate customers for the adoption of Fintech applications in an efficient way. Due to dynamic market conditions, it is difficult for the banks to win the heart of the customers. It can be done only by providing them with updated technological applications and excellent services. Here, service quality plays a major role in this regard. It acts as an optimum strategy for the service providers to attain the interest of their customers and change their perceptions towards the banks in a positive way by providing them satisfactory services. This chapter aims to critically analyse and assess the quality of banking services rendered for Fintech applications to the customers.

Design/Methodology/Approach: The study evaluated the preference for public/private banks for Fintech applications across various demographic factors. In this research, users of public or private banks have been considered as respondents who are using Fintech applications. The service quality of both banks has been measured using a service quality scale, i.e., SERVQUAL. With the help of the Questionnaire, data were collected from 100 respondents from Punjab State on a convenience sampling basis. The Chi-square method was used to check the preference for different types of banks across demographic profiles.

Findings: ‘Responsiveness’ and ‘Tangibles’ are the most significant service quality dimensions. The present study revealed that the preference towards public/private sector banks has no dependency on occupation but found dependence on age and education level.

Research Limitations/Implications: The present study merely concentrates on the banking sector’s service quality towards Fintech applications. It could be used for the security market, insurance and other sectors in the future period. The present study provides implications for future interdisciplinary research addressing the need for Fintech applications as Fintech has become the need of every industry.

Originality/Value: This study is conducted to explore the opportunities for Fintech in the banking sector vis-á-vis service quality. The authors anticipate that the current study will contribute to existing literature and thus become the reference for academicians, researchers and industry professionals.

This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.