Search results

Innovation is necessary to ensure consistent economic growth and to meet the global competition. In view of this, the purpose of this study to check the effect of governance quality as a tool for fostering innovation performance.

The empirical analysis was arranged on 20 year’s (2000–2019) data from South Asian economies. Subject to the existence of cointegration, the authors use the fully modified ordinary least square model for regression analysis and check the robustness through robust least square model.

The empirical findings infer that all dimensions of governance have a positive significant impact on both research and development expenditures and trademark applications jointly known as innovation performance. In addition, the empirical analysis discloses the positive effect of all control variables, including FDI inflow, banking sector development, economic growth, ease of doing business index and government subsidies on innovation activities. The analysis confirms the “grease the wheel” role of governance in fostering innovation.

It is apparently recommended to strengthen the exercise of better governance to harvest better innovation scores.

This study advocates the positive role of individual dimensions of governance recommended by existing literature and complements the literature by jointly exploring the impact of all governance dimensions on overall innovation performance.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

Research and development (R&D) is a vital strategy for firms to sustain their competitive locus and profitability in the global marketplace. Therefore, the existing research is engrossed in the correlation between firm performance (FP) and R&D intensity (RDI) meta-analysis. It also examined the ‘Type of Firm’ as a moderator in this relationship.

This study is motivated by its potential to address existing knowledge gaps, guide decision-making, influence policy and contribute to advancing theoretical and practical insights in the domain of business, economics and innovation.

This study is based on the secondary data. The researcher uses ‘Meta- Essentials 1.5’ for meta-analysis covering the studies of developed and emerging economies from 1985 to 2022.

The outcome conveys a small effect of magnitude between RDI and FP. It also indicates the positively significant linkage between them, directing that investing in R&D projects leads to improvement in the performance of companies. It also points out that private firms engaging in R&D activities have a negative while public firms have a positive correlation with their performance.

Understanding this linkage is imperative as it aids managers in making strategic decisions, the government in funding research-related schemes and investors in choosing R&D projects for investment.

Introduction: ‘Ecotourism’ refers to tourism that promotes and preserves a site’s eco-heritage to make tourists aware of the cultural past and protect the environment at the same time. The elementary impression behind ecotourism is that it signifies an appealing alternative to the mass tourism paradigm, significantly altering the natural and social circumstances of tourist destinations worldwide.

Purpose: To study the various factors responsible for the prospects and development of ecotourism, including marketing strategies, which necessitates and deliberates for society’s well-being and the safeguarding of the landscape.

Need for the study: This research provides perceptions into the economic, environmental, and social factors and the marketing tools that influence the sustainable development of ecotourism and to address the historical neglect or minimal consideration of environmental impacts associated with tourism practices.

Methodology: The study involved quantitative analysis gathering primary data from 100 respondents and inclusion of secondary data sourced from journals and articles. The collected data underwent testing and analysis, employing descriptive statistical analysis, analysis of variance (ANOVA), correlation analysis, and structural equation modelling (SEM). These analyses successfully established relationships among the variables under investigation.

Findings: The study recommends a futuristic plan to boost the sustainable growth of ecotourism on the basis of the findings of the study.

Practical implication: The research underscores the pivotal role of local community engagement, education, enhanced visitor experiences, and strategic promotion facilitated by eco-smart technologies in fostering the sustainable growth of ecotourism destinations.

Nuclear energy investments contribute significantly to the energy independence of countries. This situation helps countries to develop both economically and socially. Therefore, countries need to develop strategies to increase their nuclear energy investments. However, radioactive waste generated in nuclear reactors is one of the most important disadvantages of this type of energy. Due to this situation, the wastes generated must be disposed of effectively for nuclear energy investments to be effective. In this study, it is aimed to create optimal strategies for the effective waste managements generated in nuclear power plants. Within this framework, four different balanced scorecard perspectives are considered as the criteria. In the analysis process, Analytical Hierarchy Process (AHP) methodology is taken into consideration. It is identified that learning and development is the most critical factor for the effective radioactive waste management created in nuclear power plants. On the other side, internal factors are the second most important criterion in this framework. Hence, it is understood that nuclear energy investors should give priority to the technological development for effective waste management in nuclear power plants. With the help of these technological improvements, the wastes can be disposed more successfully. As a result, environmental sustainability can be provided much easily.

Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

Fintech provides the necessary ecosystem for businesses to accept payments for goods and services in the most seamless manner. It can also be said that innovation in Fintech is one of the growth drivers for businesses in today's globalised market.

Fintech is revamping the entrepreneurship business by bridging the gap between the market and real-time access to investment. It provides entrepreneurs with numerous advantages like easy access to resources, reduced expenses and better customer experience. Hence, this research has focused on evaluating the impact of Fintech business on entrepreneurship business in the global market.

A mixed method of data collection has been used to conduct the research in which primary data have been collected using an online survey and secondary data have been collected from online articles and peer-reviewed journals. An online survey of 51 business managers recruited from the social networking platform LinkedIn has been done to collect primary data. Secondary data have been collected from the online database Google Scholar which has been published in the last five years.

The findings of the study have highlighted the various impacts that Fintech has had on entrepreneurship business in the global market and the reason why it is such an important factor for growth.

This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.

Small and medium-sized enterprises (SMEs) use networks to overcome knowledge deficiencies in pursuing innovation. However, balancing the cost and risk of growing networks, especially internationally, with potential gains in knowledge remains a critical challenge. Searching for innovation knowledge in international and domestic networks can be complementary when learning is compressed or as competing when the SMEs capacity to use the new knowledge is exceeded. This paper aims to investigate whether knowledge searches in domestic and international networks are complementary or conflicting in pursuit of innovation.

This study is based on firm-level data set comprising 426 SMEs located in New Zealand, an advanced small and open economy. Using multi-level modelling, this study tests competing hypotheses, asking whether domestic and international network searches are complements or substitutes when seeking ambidexterity.

The research finds that, in contrast to earlier research, which shows increasing network breadth drives innovation activity, SMEs benefit less from knowledge search across combined domestic and international networks for exploration innovation and ambidexterity. In contrast, exploitation shows no effect, suggesting that combined networks could support exploitation.

This paper highlights how SMEs mitigate the influence resource constraints have on the partnerships they form and how this translates to ambidexterity. Specifically, recognising that an opportunistic approach to network development may impose future constraints on SME ambidexterity. From a management perspective, the paper recognises that balancing knowledge search across domestic and international networks can facilitate ambidexterity; however, to prevent spreading resources too thinly, this likely requires exit from early domestic innovation network partnerships.