Political representation is responsible for choices regarding the supply and the management of transport infrastructure, but its decisions are sometimes in conflict with the will and the general interest expressed by citizens. This situation has progressively prompted the use of specific corrective measures in order to obtain socially sustainable decisions, such as the deliberative procedures for the appraisal of public goods. The standard Stated Choice Modelling Technique (SCMT) can be used to estimate the community appreciation for public goods such as transport infrastructure; but the application of the SCMT in its standard form would be inadequate to provide an estimation that expresses the general interest of the affected community. Hence the need to adapt the standard SCMT on the basis of the operational conditions imposed by deliberative appraisal procedures. Therefore, the general aim of the paper is to outline the basic conditions on which a modified SCMT with deliberative procedure can be set up. Firstly, the elements of the standard SCMT on which to make the necessary adjustments are identified; subsequently, modifications and additions to make to the standard technique are indicated; finally, the contents of an extensive program of experimentation are outlined.
Business ethics plays a crucial role in developing modern business and the entire society. Thus, to develop the conceptual framework of business ethics, it is extremely interesting to study the concepts connected with it. The article identifies the main terms and concepts associated with business ethics. On this basis, the authors’ conceptual framework of business ethics was created. Within this conceptual framework, it is shown that each business unit builds and maintains relationships with stakeholders within two “circles of business ethics”: the inner circle of business ethics and the outer circle of business ethics. The article proves the hypothesis that business ethics should be considered in the context of relationships with all stakeholders, i.e., it is the ethics of business relationships with partners and competitors in the external environment, as well as within the internal environment (primarily with employees). The article will be of interest to specialists in the field of management, and corporate governance, as well as for anyone interested in the problems of corporate social management.
Electric cars are manufactured to address environmental problems, reduce dependence on fossil fuels, and nullify climate change. Their production aligns with sustainability objectives by encouraging cleaner transportation options, promoting energy efficiency, and contributing to a transition towards eco-friendly mobility in an answer to global environmental challenges. In Jordan, similar to any international market, car dealers and traders import electric cars. However, the prevailing perceptions and attitudes of Jordanian consumers need strong consideration. Nevertheless, there is still uncertainty and a need for more trust in electric vehicles among Jordanian consumers. Therefore, this research aims to ascertain whether electric cars have a lasting positive perception among Jordanians through an inductive research approach. Employing thematic qualitative analysis, this research is supported by the diffusion of innovation theory. Notably, the research findings provided robust insights, further leading to reinforcing the idea about the pervasive attitudes of Jordanian consumers. Thus, this research concludes that there still needs to be more confidence regarding electric vehicles among most consumers in Jordan. Furthermore, this research offers practical and theoretical contributions to Jordan’s policymakers and electric vehicle companies.
The study investigates the impact of artificial intelligence (AI)-powered chatbots on brand dynamics within the banking sector, focusing on the interrelationships between AI implementation and key brand dimensions, including awareness, equity, image, and loyalty. Using structural equation modeling (SEM) analysis on data collected from 520 banking customers, the study tests eight hypotheses to explore the direct and indirect effects of AI-driven interactions on brand development. The findings reveal that AI chatbots significantly enhance brand awareness in banking services, demonstrating moderate positive effects on both brand equity and brand image. Notably, while brand awareness exerts a strong influence on brand image, it does not have a significant direct effect on brand loyalty. Instead, the study shows that brand loyalty is primarily developed through the mediating effects of brand equity and image, with brand image exerting a particularly strong influence on brand equity. For banking practitioners, these insights suggest a need to integrate AI chatbots within a comprehensive brand strategy that merges technological innovation with traditional relationship-building approaches. Limitations of the study and potential directions for future research are also discussed, providing avenues for further exploration of AI’s role in brand management.
Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.
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