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The chapter looks at policies regarding access to higher education (HE) for the Palestinian Arab minority in Israel (PAMI). Recently, HE among PAMI has expanded compared to previous years, but the proportion of PAMI students in Israeli institutions of HE (14%) is still not equal to the percentage of PAMI (20%). The Council for Higher Education (CHE) in Israel has been trying to increase the accessibility of PAMI students in institutions of HE through the implementation of several projects and academic programs and the expectation of reaching 17% in 2021. The chapter has three main aims: (1) to describe the decisions and recommendations of CHE for increasing the rate of peripheral students in HE, (2) to trace their implementation in HE institutions, and (3) to investigate the influences of these policies in schools through interviews with secondary school principals and secondary students in PAMI schools to understand how they act to improve students’ awareness of these initiatives and to improve access to HE for their graduates. A qualitative-phenomenological study analyzes policy guidelines regarding HE for PAMI as set out by the two main committees established by the Israeli CHE. The findings may have international significance since similar difficulties are encountered in access to HE among underprivileged or peripheral populations in other world states.

The aim of the study is to determine the benefits of transforming a destination into smart destination (SD) to restart tourism after the COVID-19 outbreak, to match the dimensions of SD with restarting strategies, and to make conceptual inferences to serve this. For this purpose, two reports published by the World Tourism Organization (WTO) in 2020 were examined: Priorities for Tourism Recovery and Global Guidelines to Restart Tourism. Then, the contents of these reports and the dimensions of SDs were matched and a guiding model for tourism decision-makers was developed.

Concept maps are popularly used within academic development spaces, especially to teach new concepts at beginner levels for undergraduate students. Their popularity is partly based on the fact that they employ visual tools such as charts, diagrams, pictures, tables, etc., to simplify concepts that students would otherwise consider dense. This paper reports on the findings of an extended orientation project conducted between February and June of 2022 with a small cohort of 15 first-year students registered in an entrepreneurship course at a vocational higher education institution in South Africa. The research question guiding this study is: How can concept maps inspire entrepreneurial thinking for first-year ECP students at a vocational institution in South Africa? Using Cultural-Historical Activity Theory (CHAT), I analysed the two iterations of the students' concept maps together with selected data from the focus group interviews. Key findings reported include the students' fuzzy knowledge of what entrepreneurship as a discipline entails, the planned career trajectories for most of the participating students, as well as indecisiveness as to whether the students will be pursuing entrepreneurship after graduation. In the language of CHAT, the above findings are described as presenting tensions between the subject, tool and object. This layer of analysis calls for an urgent re-think of how the students are recruited and orientated into the programme and how the curriculum is delivered at the first-year level.

With the ever-growing population in the urban areas, the concept of smart cities started to be more present in the literature. Smart cities are seen as a solution that will respond to the needs of providing a sustainable place for living, and at the same time improving residents’ lives. To achieve this, various information and communication technologies (ICTs) are exploited, making the digitalization in the modern world of an immense importance. Advanced digital technologies enable the transformation of existing and the creation of new business models, the development of new products and services, increase the efficiency and competitiveness of the economy, and contribute to wider socio-economic development. Digitization of society and the economy through innovative and intensive use of ICTs has great potential for growth and is the basis for further development and competitiveness. This all generates an enormous amounts of data sets from which useful information are generated and used again the decision support systems. This chapter presents two examples from Slovenia where big data is used for improving residents’ lives, as part of the strategies for smart cities.

Innovation means innovation. It enables companies to grow and compete with other companies. However, innovation studies also increase the welfare level of the countries. One of the most important topics in innovation studies is research and development (R&D). R&D enables companies to identify their current problems and lay the groundwork for new products and services. In this way, it contributes to the profit of the companies. The purpose of this study is to determine the effect of innovation on the share value of the company. In the study, the data are collected from Turkey during the period 1991–2019. However, the study was tested by Engle–Granger Cointegration analysis. As a result, it has been determined that there is a long-term relationship between R&D expenditures and the company’s share value. In this context, companies need to focus on R&D expenditures to increase their share values. For this issue, they need to increase their liquidity. In addition, the R&D departments in the company need to be increased. Companies need to prepare a separate budget for R&D studies.

Recognising the significance of international trade in economic growth, this research explores the drivers of exports in South Asian Association for Regional Cooperation countries from 2008 to 2021. The study employs the export demand model and the augmented exports supply model and utilises pooled time-series data. This study questions whether export supply decisions are based on traditional trade model factors, emerging trading realities or macroeconomic variables. The model based on fixed effects evaluates the connection between exports and their possible drivers. Traditional export supply models suggest determinants like production capacity, variable cost and relative pricing influencing South Asian export supply performance substantially. Changes in trade, for example, have a substantial impact on export supply, demonstrating that the trade liberalisation procedure promotes growth in exports, compression in imports and technological advancement. The worsening state of the energy industry and growing levels of corruption have proved to be significant deterrents to export supply decisions. The results verify foreign direct investment's positive and medium influence on the expansion of exports. Other variables, however, such as GDP and its growth, Official Development Assistance (ODA), development expenditure, indirect taxation, labour supply and the exchange rate of currencies, have a positive impact on the flow of exports. Furthermore, the data corroborate the notion that increased savings have a significant beneficial influence on the flow of exports. The study proposes that concerned governments examine their export policies and adopt new policies adapted in accordance with changing circumstances with the goal of increasing and enhancing the performance of exports.

Purpose: This chapter aims to find the impact of cultural marketing on consumer buying behaviour and analyse the cultural factors affecting consumers’ buying behaviour. Cultural marketing aims to offer and promote a product, a message, or a service to a group of people who may be their potential purchasers and belong to the same culture or particular demographic.

Methodology: This study uses the published research for different countries viz. India, Canada, Germany, the UAE, the UK, the USA, Japan, etc., in the field of culture, cross-culture, and consumer buying behaviour considering various factors and their impact; but in particular, this study focussed on the cultural factors only and analysed their impact on the consumer behaviour of the different countries.

Findings: The study revealed that different countries have their own unique culture. Cultural factors have a positive relationship with consumers’ buying behaviour and exhibit that consumers behave differently towards the same product as per their perception developed by their culture.

Need of the study: Today, the world has become global, and to become a successful consumer oriented market service provider, marketers have to study the psychology of the customers to procure them. This study focusses on one of the essential factors, that is, culture and how cultural factors affect consumer buying behaviour. The study of culture is the gateway to attracting consumers in the market.

Practical implications: The study would help multinational companies in segmentation, targeting, and positioning and developing several marketing strategies for their products. Companies would be able to understand changes in consumer purchasing behaviours that arise from cultural differences, which helps them cater to the needs of their global consumers.

In this chapter, drone and vision camera technology have been combined for monitoring the crop product quality. Three vegetable crops such as tomato, cauliflower, and eggplant are considered for quality monitoring; hence, image datasets are collected for those vegetables only. The proposed method classified the vegetables into two classes as rotten and nonrotten products so the images were collected for rotten and nonrotten products. Three different features information such as chromatic features, contour features, and texture features have been extracted from the dataset and further used to train a Gaussian kernel support vector machine algorithm for identifying the product quality. The system utilized multiple features such as chromatic, contour, and texture features in classifier training which enhances the accuracy and robustness of the system. Chromatic features were utilized for detecting the crop while other features such as contour and texture features were utilized for further classifier building to identify the crop product quality. The performance of the system is evaluated based on the true positive rate, false discovery rate, positive predictive value, and accuracy. The proposed system identified good and bad products with a 97.9% of true positive rate, 2.43 % of false discovery rate, 97.73% positive predictive value, and 95.4% of accuracy. The achieved results concluded that the results are lucrative and the proposed system is efficient in agriculture product quality monitoring.