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Introduction to Intelligent Computational Technologies

C. Geetha1, Sajithra S.1, S. Srijayanthi1, B. Reena2*, I. Subha3 and Sreelakshmi N.4

1R.M.K. Engineering College, Kavaraipettai, India

2Department of Computer Science and Engineering, Hindustan College of Engineering and Technology, Coimbatore, Tamil Nadu, India

3Zoho Labs, Chennai, India

4LBS Institute Technology for Women, Poojappura, Thiruvananthapuram, India

Abstract

Indeed, the convergence of smart technologies and sustainability imperatives is one of vital spectrum and focus in application development within the contemporary technological context. This chapter investigates the overlap in these domains by putting forward a framework for designing smart and sustainable applications via computational techniques. Building on cutting-edge Artificial Intelligence, Machine Learning, and Data Analytics technologies, it tackles challenging problems as efficiently as possible by maximizing resource utilization without compromising the environmental impact. The paper highlights some key concerns associated with the design, such as data acquisition, modeling, optimization, and deployment policy. Moreover, it discusses case studies and applications in different domains to clarify the effectiveness of intelligent computational techniques and their potential for enabling smart, sustainable development. By doing so, developers and stakeholders can work towards building novel pathways that lead to a more efficient, resilient, and environmentally conscious future. This chapter is all about gathering the right sets of elements/attributes or factors to utilize for different E-Governance services. As per this research, weak adoption factors of E-Governance have been identified and ranked using the fuzzy conjoint technique. These factors are ranked based on satisfaction levels, from highest to lowest: very satisfied, satisfied, neither/nor (ambiguous), dissatisfied, and very dissatisfied. The ranking of the above factors with satisfaction levels also defines whether the government needs to focus on or not to increase adoption.

Keywords: Smart technologies, sustainability, application development, intelligent computational techniques, artificial intelligence, machine learning

1.1 Introduction

Implementing e-services, or electronic services, will have a deeply rooted impact on every citizen of the nation. If the citizens are unwilling to consume these services, it virtually defeats the purpose of provisioning and consuming e-services as they are the primary consumers. This pressure therefore blasts the call to sieve out what factors can ascertain the suitability of such services. So, the suitable factors have already been identified by the researchers. These factors are addressed as infrastructure, cost, trust, time, accessibility literacy, language, willingness, age, gender, and people awareness [1]. The success of e-services depends on how satisfied people are with their usage. There aren't many private players in the community to meet this expectation, so we need support from the government as well. Internet connectivity, including its speed and bandwidth, is a crucial factor when implementing e-services across the country. Another thing to consider is that there are new technologies out. In the case of a multilingual country, these e-services should also be multilingual. Given the variations in demand preferences for end-users across the country, it is essential to understand what specific factors play a critical role in ensuring that consumers adopt e-services. Hence, this chapter will rank acceptance factors through fuzzy joint model statistics to address the sluggish access to e-governance services. The Fuzzy Conjoint Model was proposed by Turksen and Wilson [2] in 1994. This order of factors was also validated with other ranking approaches such as those proposed by Biswas [3] and Wang [4].

1.2 Literature Survey

Most theories are based on the Davis Technology Acceptance Model (1989) [5], the Unified Theory of Acceptance and Use of Technology, the Theory of Reasoned Action (TRA) [6], the Diffusion of Innovation, etc. Tashfeen Miral Screwvala extended the work of Carter and Belanger (2005) [7] by identifying the 'purpose of use' factor. When deploying technology-based electronic services, the security of existing information is a highly important factor. E-services [8] introduced by the government offer numerous benefits, including increased reusability of information and citizens' satisfaction by sharing it with general public. The author tested an e-governance service introduced by the city council of New Delhi, India [9]. The central idea is that, based on literature research, it can be assumed that the adoption of these services depends on how citizens perceive government electronic services. Table 1.1 lists some of the theories discussed by researchers [10] that the study or research found. Table 1.2 presents the key attributes affecting e-governance adoption.

Table 1.1 Some empirical theories about adoption models.

Model/theory Factors/items Definitions Authors A Unified Model of E-Governance Adoption (UMEGA) Perceived service quality and recommendation Recognizing the quality and trust of service to the government, as well as the intent to use and recommend e-government services. Mensah et al., 2020 [11] TAM2 (Extended Technology Acceptance Model) Thought/Image An image of a person after using an innovative service. Venkatesh, 2000 [15] Voluntariness Personal evaluation of the voluntary use of innovative services. Moore and Benbasat, 1991 [16] Job relevance Identify the system that applies to his or her work. Quality of output Comparison with the previous version. DOI (Diffusion of Innovation) Benefits How is the E-Governance service advantageous over its predecessor? Rogers and Shoemaker, 1971 [17] Complexity The system is relatively difficult to use and understand. Observability Determine the output of innovation.

Table 1.2 Factors/attributes affecting the adoption of E-Governance services.

Factors Description Authors Perceived service quality and intention to use Service quality, intention to use, and recommendations to others. Mensah et al., 2020 [11] Transaction security Transaction security when using e-government applications. Rehman M. et al., 2012 [19] Transparency/fairness Determine the transparency of electronic services. Bertot et al., 2010 [20] Corruption avoidance How much corruption will be reduced after the introduction of e-government services? Bertot et al., 2010 [20] Perceived risk Risks associated with the use of e-government applications. Be'langer, Carter, 2008 [22] Trust in the government Evaluate the level of government confidence in using e-services introduced by the government. Saxena, 2005 [23] Trust in the internet Describe public confidence in the use of the Internet and applications. Leitner, 2003 [25] Customer support Determine the level of customer support while using e-government services in case of stuck. De Ruyteer et al. 2024 [26]

Researchers have also examined the assessment of government websites, applications, and mobile apps. Jain et al. (2004) [27] proposed an evolutionary fuzzy system for evaluating supplier performance using the linguistic nature of supplier and manufacturer attributes.

Besides the various factors discussed above, some matters also need consideration, including but not limited to interoperability with other systems, resource management, and policy standardization [28]. In this context, the purpose of this chapter is to measure e-government service evaluation factors. The fuzzy conjoint model is also utilized in ranking and selecting of the suitable factors from them [2].

Conduct collaborative statistical analysis on survey data to understand the overall picture of each product and its attributes, characteristics, advantages, etc., based on columns in Likert scales like 'satisfied' and 'very satisfied'. With the survey data responses handy, you-or anyone else, for that matter-could evaluate our product as a service. Every individual has unique requirements, and according to their preferences, they tend to respond to a variety of products and services. There's no accounting for taste. Fuzzy set theory can be used for ambiguous, uncertain, and undefined tastes. As far as civic...