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The importance of fuzzy logic (FL) in approximate reasoning, and that of default logic (DL) in reasoning with incomplete information, is well established. Also, the need for a commonsense reasoning framework that handles both these aspects has been widely anticipated. The purpose of this paper is to show that fuzzyfied default logic (FDL) is an attempt at creating such a framework.

The basic syntax, semantics, unique characteristics and examples of its complex reasoning abilities have been presented in this paper.

Interestingly, FDL turns out to be a generalization of traditional DL, with even better support for non‐monotonic reasoning.

The paper presents a generalized tool for commonsense reasoning which can be used for inference under incomplete information.

The pandemic COVID-19 brought in large challenges globally among the workforce. There were reports of how employee layoffs and pay-cuts were gradually becoming prominent across industries based on media reports. However, there were no attempts to develop a typology of challenges faced by the workforce.

This study mined user-generated content from Twitter to bring out a typology of challenges due to the sudden turbulence that is faced from the pandemic. A case study has also been conducted by taking in-depth interviews in the academic sector to deep dive into the nature of these problems.

The study findings indicate that these challenges are basically stemming from challenges surrounding infrastructure readiness, digital readiness, changing nature of deliverables, workforce demand versus supply problems and challenges surrounding job losses.

There is a need to explore the linkages through inferential research infrastructure readiness, digital readiness, changing nature of deliverables, workforce demand versus supply problems and challenges surrounding job losses on employee welfare during pandemics.

The authors provide inductive insights based on a data-driven research methodology surrounding the sudden challenges faced and possible mechanisms to address these issues faced by a stressed workforce catering to multiple stakeholders.

This paper aims to enlighten stakeholders about critical success factors (CSFs) in developing intelligent autonomous systems (IASs) by integrating artificial intelligence (AI) with robotics. It suggests a prioritization hierarchy model for building sustainable ecosystem for developing IASs.

This paper is based on the existing literature and on the opinion of 15 experts. All the experts have minimum of eight years of experience in AI and related technologies. The CSF theory is used as a theoretical lens and total interpretative structure modelling (TISM) is used for the prioritization of CSFs.

Developing countries like India could leverage IASs and associated technologies for solving different societal problems. Policymakers need to develop basic policies regarding data collection, standardized hardware, skilled manpower, funding and start-up culture that can act as building blocks in undertaking sustainable ecosystem for developing IASs and implementing national AI strategy. Clear-cut regulations need to be in place for the proper functioning of the ecosystem. Any technology that can function properly in India has better chances of working at the global level considering the size of the population.

This paper had all its experts from India only, and that makes the limitation of this paper, as there is a possibility that some of the factors identified may not hold same significance in other countries.

Stakeholders will understand the critical factors that are important in developing sustainable ecosystem for IASs and what should be the possible order of activities corresponding to each CSF.

The paper is the first of its kind that has used the CSF theory and TISM methodology for the identification and prioritization of CSFs in developing IASs. Further, eight significant factors, that is, emerging economy multinational enterprises (EMNEs), governance, utility, manpower, capital, software, data and hardware, have come up as the most important factors in integrating AI with robotics in India.

The paper examines the succession management strategies and the preparation level of heirs in the context of family-owned educational institutions in Nepal.

Sixteen in-depth, semi-structured interviews with the institution's leader were conducted. Each interview was transcribed using content analysis. Several themes and new items emerged that define the institutional strategies in succession management.

The paper provides insight into the challenges of implementing effective succession management strategies. The identified themes are traits, processes, challenging aspects and effective plans. The study's findings show the lack of awareness about the importance of succession planning among the institution owners due to the availability of limited resources. The paper also provides some insights into how family ownership and management are done and the lack of formal processes in succession management strategies.

This paper offers readers the chance to think about succession planning strategies. Also, it adds value in their critical analysis of the succession plan. The study advised the learners to consider additional elements that can impact succession planning, such as experience, educational requirements and their desire to work. It will aid researchers in considering the societal perspective of the successor, which is also a significant worry.

It focuses on a specific context, private schools in Nepal, and examines the challenges they face in implementing succession management strategies. The paper tries to identify the approach that may reveal potential solutions that have not been considered. The paper aims to clearly articulate the unique contributions of the study and explain how it advances the existing literature on succession management.

Explainable artificial intelligence (XAI) has importance in several industrial applications. The study aims to provide a comparison of two important methods used for explainable AI algorithms.

In this study multiple criteria has been used to compare between explainable Ranked Area Integrals (xRAI) and integrated gradient (IG) methods for the explainability of AI algorithms, based on a multimethod phase-wise analysis research design.

The theoretical part includes the comparison of frameworks of two methods. In contrast, the methods have been compared across five dimensions like functional, operational, usability, safety and validation, from a practical point of view.

A comparison has been made by combining criteria from theoretical and practical points of view, which demonstrates tradeoffs in terms of choices for the user.

Our results show that the xRAI method performs better from a theoretical point of view. However, the IG method shows a good result with both model accuracy and prediction quality.

The importance and criticality of sustainable development goals is witnessed by 195 member countries. For its full-fledged adoption and implementation, it needs to be understood by masses and political leaders are critical agents those engage diverse communities through social media such as twitter. Therefore, in this study focuses on how political leaders can influence the sustainable development goals through Twitter.

This study examines the social media conversations of political leaders on Twitter. Social media analytics methods such as sentiment mining, topic modelling and content analysis-based methods have been used.

The findings indicate that most political leaders are primarily discussing the sustainable development goals (SDGs) “partnership for goals” and “peace, justice and strong institutions”. Many other goals such as “clean water and sanitation”, “life below water”, “zero hunger”, “no poverty” and “educational quality” are not being focused on.

This study offers implications in terms of collective decision making and the role of policy makers towards the goals of promoting SDGs. The authors highlight how political leaders need to involve key stakeholders in this journey.

This study scores and provides a cohort-specific prioritization of the leadership within these countries with regard to SDGs, which could be beneficial to the society.

Big Data has become crucial for fulfilling the vision of smart cities; however, there are several challenges associated with its use. This study aims to provide a holistic view of challenges of using Big Data in smart cities and the solutions to deal with them by systematically selecting, reviewing and synthesizing the literature in this area.

A systematic literature review was conducted by following a rigorous search protocol that identified a total of 310 peer-reviewed academic research papers. These papers were subsequently filtered and finally 38 relevant papers were selected.

A number of major challenges (human dynamics, privacy, security, volume, velocity, variety, veracity and value) associated with Big Data in a smart city and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing Big Data in smart cities.

The study provides valuable information to the Big Data practitioners by illustrating the process of effective management of Big Data in smart cities. This study further provides the directions to the future researchers.

The study is original and is based on the existing literature and its interpretation.

The chapter discusses how adolescents are moving beyond the dichotomy of biological and linguistic socialization, forming interpretive meanings at home through the reading of literature in their mother tongue, Bengali. Involving cultural relevance and non-vulnerability, the chapter conceptualizes “leisure activities” and “leisure pursuits” of reading practice of the IXth and Xth graders from both Bengali and English medium schools in Kolkata. The discussion from the theoretical construction mentions the further conceptualization of reading habits and language choice. This is where adolescents derive their agency. Adolescents from the Indian and especially from the Bengali perspective have a path of colonial discourse. From historical standpoint, the change in Bengali language and its grammar structure has influenced the acceptance of Bengali literature among adolescents in varying degrees through generations. Using mixed methods and content analysis, the chapter focuses on young teenagers’ narration on the way they maneuver curriculum and literature in their respective homes. Authors, for example, Sunil Gangopadhyay, Satyajit Ray, and Bibhutibhushan Bandyopadhyay, form the Bengali identity construction in the present time. Rabindranath Tagore’s, Sarat Chandra Chattopadhyay’s and Bankim Chandra Chatterjee’s works are always prevalent in the Bengali language syllabus. These are considered the foundational modern literary figures of pre-independent India. These are taught from a nationalist and gender discourse perspective. The adolescents in this chapter also read those at a minimum level at home and attempt to juggle the difficult vocabulary involved. The simple language of post-independent literature is much sought after by teenagers compared to pre-independent literature. Sunil Gangopadhyay’s Kakababu series, Satyajit Ray’s Feluda and Professor Shanku series, and Bibhutibhushan Bandopadhyay’s Chander Pahar stand out among the adolescents from both English and Bengali medium unanimously in this chapter.

The aims of this paper are to provide an integrated literature review of factors influencing consumers' responses to brand websites; to describe the state of research in the past ten years; and to give an overview of the theories used in brand website studies.

Using a vote‐counting procedure, 736 findings from 50 empirical studies are synthesized. In a vote‐counting analysis the number of positive and negative significant relations between the same two variables is compared to the number of non‐significant relationships.

The analysis reveals which person‐related factors (e.g. involvement or flow) and website‐related factors (e.g. usability or interactivity) influence responses to websites and brands. To explain such responses many studies integrate new theoretical concepts (e.g. interactivity or telepresence) into traditional theories. Furthermore, the review shows that the current state of research is limited by the use of forced exposure, student samples and the measurement of affective responses.

The present study investigates an increasingly popular approach to promote brands at the internet: the use of brand websites. The study gives insight into factors influencing the effectiveness of these websites. Marketers can use this knowledge to improve the effectiveness of their websites.

The paper provides a valuable contribution to the literature on brand websites. The paper can form the basis for future research on this topic.

Placement prominence is a multidimensional concept. Previous studies have defined and operationalized prominence in different ways, and no studies have tried to systematically examine what should and should not be counted as prominence. This study aims to fill this gap.

Using a content analysis of six short films and a survey study on 129 Chinese young adults, this study systematically examined 13 dimensions of placement prominence on the memory of placed brands.

Factor analysis has reduced the 13 dimensions into five factors: contextual, narrative, sensory, exposure and spatial prominence. Fuzzy-set qualitative comparative analysis (QCA) software was used to conduct a contrarian case analysis and test for predictive validity. This was followed by a QCA to identify the optimal configurations of the five factors that may lead to a high recognition of the placed brands. The optimal configurations were also contrasted across two gender and brand familiarity groups. While the optimal configurations of prominence on brand memory for male and female participants were largely the same, the combinations differed between participants with low and high brand familiarity.

Previous studies in product placement usually operationalize prominence with a few dominant dimensions intuitively though several other dimensions, and their interactions could also affect the prominence level. To the best of authors’ knowledge, this is the first study that used multiple dimensions of prominence configurations to identify paths that may lead to low and high brand memory. The empirical results contribute to the theory and understanding of the effect of prominence on brand memory and provide guidance to brand managers in determining which prominence configuration is the most suitable for achieving their promotional objective.