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Unveiling the Factors of Women Entrepreneurs on Social Media to Achieve Enterprise Sustainability
The research studies in the area of womens entrepreneurship (WE) has received more attention in the last decade due to its impact on bringing balanced development. On one hand, the growth of digital innovation has changed the landscape of entrepreneurship in emerging markets and on the other hand, the advocacy on business sustainability has increased. Prior studies are limited to understand the role of WE in this changing landscape. This study aims to identify the most relevant factors that influence the women entrepreneurs on social media to develop sustainable enterprise. An extensive literature review has been conducted to advance the knowledge on the WE and has been presented in form of a conceptual model to present a comprehensive perspective. Further, the research identifies social factors, psychological factors, resource factors, financial factor, firm-performance related factors, and technological factors. These factors are linked with entrepreneurial orientation among women on social media and therefore this helps in gaining sustainability. These study further present implications, strategies and agenda for future research in the area of WE. 2025 selection and editorial matter, Esra Sipahi Dongul, Serife Uguz Arsu, Richa Goel, and Tilottama Singh; individual chapters, the contributors. -
Key Motivational Factors Driving the Adoption of Buy Now, Pay Later (BNPL)
This research paper looks into the factors influencing motivation to use Buy Now, Pay Later (BNPL) facilities. Quantitative method was employed for the survey of 223 respondents through an on-line questionnaire to determine salient factors including easy access, low or zero interest rate support offers as well as marketing and promotional strategies impact financial performance; whereas peer pressure matures a relationship between ease full comfort acceptance directly proportional with technology savvy. Top BNPL predictors in analysis: Access/convenience Low or zero interest rates Tech-savvy Peer effect and schemes to promote discount do influence but are less significant. This study offers pragmatic insights for BNPL providers, suggesting the necessity of offering a simple entry channel and low interest rates but targeting tech consumers by using social approaches or promotion tactically. These results contribute to a refined conception about consumer behavior in the BNPL market and indicate future areas of research that could be relevant for any type of consumer finance products. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Determining the most important indicators affecting the failure risk of conventional and sharia rural banks
This study identifies key variables influencing the risk of failure in Indonesia's Conventional and Sharia Rural Banks (BPR and BPRS) and proposes strategies to mitigate these risks. Using the Analytical Network Process (ANP) method, the study engaged 11 respondents, including banking practitioners from Conventional and Islamic Commercial Banks, Rural Banks, Islamic Rural Banks, and academics. Data were analyzed with Super Decision software and Excel. Results reveal four critical variables: 1) macroeconomic, 2) microprudential, 3) macroprudential, and 4) bank internal variables. The welfare aspect of macroeconomic variables emerged as the most significant, followed by the liquidity indicator in microprudential variables and the internal resilience indicator in macroprudential variables. These findings guide strategies to enhance banking performance and reduce failure risks. Regulators and the government should prioritize macroeconomic welfare indicators to strengthen the banking system and address factors contributing to BPR and BPRS failures. 2025, IGI Global Scientific Publishing. All rights reserved. -
A Systematic Approach for Predicting Cybersecurity Attacks in IoT using CNN-LSTM with HABCABO
IoT has transformed how devices work together. Now, billions of connected devices may share data across smart homes, energy systems, and environmental monitoring. In Internet of Things ecosystems, rapid IoT expansion has made them very vulnerable, which makes them easy targets for cyberattacks. Hackers can break into IoT devices that don't have enough protection to stop services, steal data, and invade privacy. This paper shows how to use deep learning using CNNs and LSTM networks and the HABCABO optimization algorithm to deal with these new dangers. After careful sequencing, scaling, and noise reduction, filter-based feature selection uses statistical methods to keep the most important information. To get the best detection, the CNN-LSTM model is trained with features that are carefully regulated. The suggested model is more accurate than CNN and LSTM approaches, with an accuracy rate of 98.04 %. These results show that the model can find and stop IoT cybersecurity threats. In conclusion, CNN-LSTM and HABCABO are strong and smart ways to make sure that IoT infrastructure is safe and reliable right now. 2025 IEEE. -
Enhancing Human Resource Management With Fuzzy Logic and Neural Networks for Personalized Performance Management
Human resource management (HRM) encounters that is making more challenging some exact, fair and person related performance appraisals on a large scale. Traditional methods often fail to capture the richness of human behaviour and tend to be opaque to interpretation. The proposed study contributes a new hybrid approach of Fuzzy Logic and Neural Network for enhanced personalized performance management. The facts are presented qualitatively by the fuzzy inference system in linguistic terms while for numerical features, the neural network analyses such that it can find complex relationship patterns. This methodology ensures the simplicity and high predictability. The model trained on Kaggle dataset achieved an accuracy of 94.7%, F1-score of 0.942, precision of 0.945, recall of 0.940 and AUC-ROC of. 976 which were higher compared to baseline approaches like Logistic Regression and Decision Trees respectively. The solution helps HR professionals make sense of relevant information into employee performance and developmental needs, which are highlighted in real time. The results suggest that combining rule-based reasoning and machine learning enhances personalisation and offers more transparent human resources practices. This study provides a foundation for the next generation of intelligent HRM systems enabling adaptive decision support in various organizational settings. 2026 IEEE. -
Digital entrepreneurship in modern techno world: mapping the literature and future research agenda
Digital entrepreneurship (DE) leverages internet services for business and financial gain. This study reviews past research, highlighting trends and gaps. Using the POWER framework and PRISMA techniques, 733 articles were analysed with VOSViewer and manual text analysis. Key findings include 2023 having the most publications, the UK leading in published articles, the journal Technological Forecasting for Social Change having the highest impact, and A. Ghezzi being the most influential author. Trending topics are entrepreneurs, digital entrepreneurship, and sustainability. Emerging themes include digital entrepreneurship ecosystems, opportunities for women and education, entrepreneurial funding, government adoption, and digital technologies. Future research should focus on entrepreneurial education, AI innovations, digital venture performance, and IoT adoption. Frameworks like lean start-up, business model innovation, and value creation can enhance DE performance, with further exploration encouraged by the identified future research agenda. Copyright 2026 Inderscience Enterprises Ltd. -
Journey to Transportation and Logistics Management Using Drone
The speedy adoption and amalgamation of drone technology in every sector of life have correlated environmental implications. It has come to reality due to revolutionization on the technology front and the movement for a digitized world by adopting digitization in the course of action. The drones have the capacity to decrease the rate of carbon emissions at significant levels in transportation and logistics management. So, this is becoming the need of an hour to apply the technology for the well-being of an individual. The comprehensive study and assessment in this chapter will address the implications of an environment connected to drone-based transportation and logistics operations. It will comprise the assessment based on academic studies, industry reports, and environmental assessments in terms of carbon emissions, energy consumption, and ecological footprint. The chapter will highlight the concerns and contributions in view of mitigating the environmental implications linked with the deployment of drones in transportation and logistics, enabling stakeholders to develop strategies that foster sustainability in the industry. 2026 Scrivener Publishing LLC. -
Efficient management of feed resources using data mining techniques /
Feed is the largest input in any livestock enterprise and the rapid increase in feed prices and shortage of feed resources has been one of the major constraints for farmers, livestock industries, planners and the policy makers. This calls for prudent management of available resources and application of computing techniques can be one of the possible potential approaches. India is endowed with a wide range of feed resources varying widely in their composition and utility for different livestock species. Clustering of feed resource into different groups based on the composition can help in better feed management. To evaluate and to suggest a best technique for clustering feed resources, we have evaluated three clustering techniques viz. K-means, spectral k-means and auto spectral on two different data sets containing 236 and 106 feed resources with major constituents like crude protein, crude fiber ash, fat etc., . -
Cutting across the Durand: Water dispute between Pakistan and Afghanistan on river Kabul
All nations firmly believe in the absolute sovereignty over the waters flow in their areas and that only riparian states have any legal right, apart from an agreement, to use the water from the shared river. To address some of their water concerns, the co-riparian states compete to have more quantity of waters. Significantly, no water agreement exists between upper riparian Afghanistan and lower riparian Pakistan, despite sharing nine big and small rivers. The simmering water dispute between them on the River Kabul is rarely noted mainly because it is overshadowed by their political tensions, differences, and the dispute over the Durand Line. Using an analytical framework, this article examines three aspects of the River Kabul water dispute: its context, identifying the challenges that hinder a formalized bilateral agreement from being implemented, and its future. 2020 Policy Studies Organization -
A comparison of recommendation algorithms based on use of linked data and cloud
Recommendation generation is a critical need in today's time. With the advent of big data and the increasing number of users, generation of most suitable recommendation is essential. There are many issues already associated with recommendations such as data acquisition, scalability, etc.. Moreover, the users today look to get best recommendations at the minimum effort on their side. Thus it becomes difficult to manage such huge amount of information, extract the needed data and present it to the user with least user involvemen t. In this research, we surveyed some recommendation algorithms and analyze their applications on an open cloud server which uses linked data to generate automated recommendations. 2018 Authors. -
KESMR: A Knowledge Enrichment Semantic Model For Recommending Microblogs
In today's world, there's an enormous amount of information available on the Internet. Because of this, it's become really important to come up with better and smarter ways to search for things online. The old-fashioned methods, like just matching certain words or using statistics, don't work so well anymore. They often suggest web pages that are irrelevant. As the Semantic Web keeps getting bigger, it needs algorithms for the best fit. In this paper, a way to measure how different the words used for web search. This helps in suggesting the most relevant web pages. A special algorithm that can change its settings. Our proposed method demonstrates 94% accuracy. 2023 IEEE. -
The repercussions of teaching in the digital era: A boon or bane?
Recently, the world has experienced a big change due to the pandemic controlling our lives. The change is also experienced by the education sector. The pandemic has forced the whole system to go digital overnight. Although the learning system has been slowly moving towards digitalisation for a considerable period of time now, the social media platform is taking over the traditional method of learning. The study has 61 respondents and the data is collected through a questionnaire. The paper applies regression analysis with the help of SPSS. The development of digital learning platforms provides an alternative to offline learning. This recent spread of the e-learning environment was fast forwarded in the COVID period. The independent variables of the paper are professional skills and ethical proficiency in online learning. These challenges are evaluated, and their impact is assessed on the learning outcome. The chapter limits its approach to professional and ethical scales by ignoring the other important variables that decide the learning outcome of the students. However, the current body of literature has a very narrow approach to the learning system. So, the chapter inspires us to cover the gap through the proposed framework model for teaching practices in the digital era. The chapter intends to develop the teaching skills and moral conscience of the academicians and ease the learners into the new path of education. The future scope makes it definite for the growing learners to understand the advancement in technology and its repercussion on the skill development process. 2024 River Publishers. All rights reserved. -
A study of parenting behaviour and children's well-being in urban India families
The aim of the research is to study parenting behavior and children’s well-being in urban Indian families. Socialization, an important process in parent-child relationship is described as, ”the process by which a child or other novice acquires the knowledge, orientations, and practices that enable him / her to participate effectively and appropriately in the social life of a particular community” (Garret & Baquedano-Lopez, 2002, p. 339). Hence, socialization in the family is of crucial significance as it is the microcosm of society and has critical implications for the social and emotional development of the growing child. Parenting is a crucial process in family socialization. The word ‘parenting’ derives from the Latin verb ‘parere’ which means ‘to bring forth, develop or educate.’ Hoghughi, M. (2004) defines parenting as “purposive activities aimed at ensuring the survival and development of children.” It is of utmost importance to understand the dynamics of the parenting in varied cultures. -
Trademark Confusion in the Era of Big Data Algorithmic Branding: Consumer Decpetion and Conpetition Law Challenge
This chapter, per the authors, examines how Big Data and AI have transformed trademark deception from sign-based imitation to algorithmically driven perception distortion. It explains how digital platforms collect and analyze massive behavioral datasets to rank, recommend, and position brands in ways that influence consumer belief about origin without copying any mark. Algorithmic practices such as competitor keyword bidding, recommendation bias, and ranking manipulation generate large-scale confusion by shaping what consumers see first and trust most. While global jurisprudence, including the LOrl v. eBay decision, recognizes platform-facilitated deception, Indian law still interprets confusion through traditional frameworks distinguishing infringement of the mark from deception of consumer belief. This chapter, per the authors, argues that AI-mediated market architecture produces deception without infringement, creating evidentiary gaps and competitive distortions that require algorithmic transparency, marketplace accountability, and an updated trademarkcompetition interface Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
SUM SIGNED GRAPHS II
In this paper, the study of sum signed graphs is continued. The balancing and switching nature of the graphs are analyzed. The concept of rna number is revisited and an important relation between the number and its complement is established. 2023, Krasovskii Institute of Mathematics and Mechanics. All rights reserved. -
Sum Signed Graphs, Parity Signed Graphs and Cordial Graphs
Signed graphs are graphs with every edge is signed either positive or negative. Given an n vertex graph, the vertices are bijectively labelled from 1 to n. A signed graph is a sum signed graph if and only if every edge is signed negative whenever the sum of the vertex labels exceeds n and every edge is signed positive whenever the sum of the vertex labels does not exceed n. For a parity signed graph, an edge receives a negative sign, if the end vertices are of opposite parity and a positive sign otherwise. Cordial signed graphs are the ones with the difference between the total number of negative edges and the positive ones is at most 1. We discuss the connection between sum signed labeling with parity signed labeling and cordial labeling. The absolute cordial condition for graphs satisfying sum signed labeling will be analyzed 2023, IAENG International Journal of Applied Mathematics.All Rights Reserved. -
Negative Domination inNetworks
We introduce s-domination in signed graphs which is based on the number of negative edges between the dominating set and its complement. The s-domination in both the positive and negative homogeneous signed graph will be studied for each value of s. As a special case, the properties of s-domination in sum signed graphs will be analyzed. The maximum value of s for a graph for which the s-domination exists is identified. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Sum signed graphs - I
Let G=(V,E) be a simple graph, f: V(G) ? {1, 2, ..., |V(G)|} be a bijective function and ?: E(G) ? {+,-} be a mapping such that ? (uv)=+, whenever f(u)+f(v) ? n and ? (uv)=-, whenever f(u)+f(v)>n. Then, S=(G,f,?) is said to be a sum signed graph. In this paper, we initiate the study of sum signed graphs. Also, we find rna number for some classes of graphs and present some of the characteristics of sum signed graphs. 2020 Author(s).