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Science and technology are transforming our world in ways that have not been seen in a long time, and we live in a rapidly changing world. Despite these changes, as citizens of today, we must not lose sight of the reality that these changes even cause crises that must be managed in order to place ourselves in a true working environment that allows us to survive as employees despite these changes. The main objective of this research is to find the relationship between interpersonal competences and teacher performance in a sustainable university. The methodology used was the quantitative, nonexperimental approach, as the variables will not be deliberately manipulated. In order to verify whether or not there was a relationship between these variables, 84 teachers from the Universidad Nacional Santiago Antunez de Mayolo were surveyed to evaluate the variables under study. The results obtained show a direct and significant relationship (Spearman's Rho = 0.731) between the two variables. Through this research, it was possible to determine that teachers who have developed interpersonal competences have a better performance, while in the relationships between interpersonal competences and the dimensions of teacher performance, a positive correlation was obtained.

The study set out to understand how the regional competitiveness index (RCI) in the department of Ancash related to the human development index (HDI) from 2008 to 2021. For a more complete understanding of the findings, each component or dimension of the RCI was analyzed. Ancash's HDI and its competitiveness index over a 14-year period were used as the population for this applied, longitudinal, descriptive-correlational study, which was based on secondary data extracted from the “Instituto Nacional de Estadística e Informática” (INEI) and business school of the Pontificia Universidad Católica del Perú (CENTRUM) statistical databases. Multiple linear regression was used to find the relationship. The research found a strong and positive correlation between regional competitiveness and human development between 2008 and 2021. No correlations were found between the HDI and the health, education, employment, or institutional dimensions of regional competitiveness, but direct and significant correlations were established between the economic environment and the HDI and between the infrastructure dimension and the HDI.

Many scholars and practitioners in the fields of business and management have recently published theoretical and empirical studies on the subject of business culture and its impact on its growth and effectiveness; yet, there has been a dearth of research on the topic of how organizational culture affects productivity. Moreover, there are hardly any theoretical or empirical research that examines these two concepts within the context of a micro-enterprise. This chapter uses a sample of 279 Ancash Region microenterprises to investigate the effect of local entrepreneurial culture on businesses’ overall performance. Among the four types of entrepreneurial cultures studied, only the Hierarchical culture was shown to have no effect on the degree of performance of the microenterprises. There is evidence of a significant causal relationship between the variables studied, the coefficient of determination was; business performance (r² = 0.796), with an SRMR of 0.037, the confirmatory model is relevant within its range of accuracy, while market culture has the greatest impact on business performance.

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.

As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.

Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.

This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

Chatbot technology is growing swiftly across the banking and finance industry. The study aims to explore the influence of Task-Technology Fit (TTF), system suitability, perceived usefulness, social influence and satisfaction on respondents’ continuance intention among the chatbot-users. A total of 250 responses were collected using a structured questionnaire via social media across India. The measurement model was proposed based on the system usability (SUS) and TTF model with other constructs, and the hypothesis was tested using a structural equation model. The findings of the study highlighted and confirmed the association among five constructs: TTF, SUS, perceived usefulness, social influence, on satisfaction and continuance intention in the context of chatbots usage in banking.

Microenterprises (MEs) are vital to the growth and prosperity of economies around the world. All levels of society, from universities to national governments, have collaborated to improve the chances of survival and future growth of these businesses. The threat to life is serious, and unless concerted action is taken, the situation will spiral out of control. Policymakers and business leaders must work together to address the sustainability crisis. The study, therefore, set out to determine how various entrepreneurial skills (such as creativity, collaboration, networking, and risk-taking) affect the long-term viability of MEs. The overall objective of the study was to determine the importance of innovative problem-solving, collaboration, networking, and willingness to take calculated risks of microentrepreneurs for the long-term success of their businesses. A total of 274 microentrepreneurs in rural areas of the Ancash region of Peru were surveyed in the grocery, hardware, clothing, and food service sectors. The survival of the MEs was tested on four dimensions: innovation, leadership, networking, and risk-taking. According to the results, MEs managers can increase their longevity by cultivating creative skills, strengthening leadership as a key to business sustainability and survival, maximizing the use of networks to gain a market advantage and expand their customer base, and employing calculated risk-taking.

Financial inclusion in Peru has been addressed through coverage, quality of financial services, movement of transactions, and service points. The purpose of this chapter is to evaluate for the department of Ancash, Peru, the link between financial inclusion and its socioeconomic factors. Socioeconomic variables and financial inclusion of the Ancash department of the National Household Survey are taken as indicators, later contrasted through the logit model, with the financial inclusion variable being the explained variable.

There is evidence of positive and negative relationships between financial inclusion and socioeconomic variables; these are important components for planning financial inclusion. Raising the levels of formal employment, the educational level and considering the area of residence would be a strategy to generate a dynamic of inclusion in the department of Ancash.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

For decades, the fast population growth worldwide was interrelated with the adopted rapid lifestyle behavior that relies on the extensive use of fossil fuels. This primary energy source has caused various urban and environmental impacts, such as global warming, air pollution, and so forth. Consequently, the identified circumstance issues have caused many health, social, and economic hindering effects for global citizens. It poses an existential threat to humanity and the global earth's ecosystem. The alarming levels of urban pollution emissions are putting enormous challenges to the related stakeholders (governments, businesses, investors, automakers, and citizens) to admit the need to decarbonize the global economy and reach sustainable development goals (SDGs) for cleaner and smarter cities across borders. As such, a vital part of a smart city is the transport sector. The road transport sector, precisely, is one of the primary consumers of fossil fuels that contribute to high carbon dioxide emissions. Accordingly, it is essential to adopt novel and sustainable urban transport solutions and promote the achievement of the SDG's eleventh goal for sustainable cities and communities. This chapter provides insight into the present global energy situation with particular attention to the road transport sector. Indeed, it highlights different emerging technologies for a sustainable and smart urban mobility future that will mitigate the environmental situation thanks to the development of drive and internet telecommunication technologies. Furthermore, we aim in this chapter to study the international progress of the transition project using the Political, Economic, Social, Technological, Environmental, and Legal (PESTEL) analysis methodology. This study is to pinpoint opportunities for project development and the challenges that set back its evolution.

Purpose: The concept of sustainability in the livelihood of rural people is the central point for the discussion for policymakers. Different policies for poverty reduction, developing economies, and environment management are not capable of using multimedia technology for rural entrepreneurial development.

Need of the Study: The study analyses the impact of multi-media and tries to understand its significance for rural enterprises to contribute to developing entrepreneurship in rural areas to minimise poverty.

Methodology: This research analysed a framework that highlights that multi-media technology offers different ways to earn a sustainable livelihood by enhancing the range of advanced technology, access to information assets, increased social networks, information transfer system, and modernisation of traditional working. A total of 450 rural entrepreneurs were contacted to collect the data from 6 different divisions of Haryana through a questionnaire on 5-point scale. A purposive sampling technique was used for primary data collection.

Findings: The multi-media technology influences rural entrepreneurial development through certain organisational factors, new products and services, improved customer service, generation of employment opportunities over time, increased loyalty, and novel combination of resources within the specific context.

Practical Implications: The study concludes the capabilities may be utilised up to maximum advantages that increase with the use of multi-media technology in the rural framework.