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The primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.

This study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.

The research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.

Despite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.

The research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

The aim is to analyze the European eco-management because the global warming has become a topical issue impacting the whole world. Individual countries are trying to minimize all the catalysts of global warming, such as carbon emissions. This paper addresses this issue and analyzes the performance of European eco-management for the purpose of future energy investments being environmentally.

This paper develops a fuzzy decision-making model to study the performance indicators of selected countries based on EMAS III standard. It employs interval type-2 fuzzy DEMATEL to evaluate the performance factors and TOPSIS methodology to assess five selected European countries' performance in relation to eco-friendly, emission and renewable energy.

Eco-friendly energy plays the most critical role in this respect followed by emissions and renewable energy which constitute significant factors. The novelty of this study is identifying significant criteria regarding environmental and energy efficiency of investments and making performance assessments of European countries with a new fuzzy decision-making model. Both expert opinions and datasets are used for the analysis. This paper supports previous research about energy efficiency investments in Europe.

The innovative feature of this study is identifying significant criteria regarding environmental and energy efficiency of investments and assessing the performance of European countries with a new fuzzy decision-making model. The fact that the analysis only concerns the European region is an important limitation. In future analyses, other groups of countries can be examined. Innovations can be made regarding the method applied. In this context, analyses can be done utilizing different fuzzy numbers. Finally, the importance of the criteria can be calculated with other methods such as SWARA.

The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments is done in this manuscript.

Analysis of European eco-management performance was done for environmentally friendly and efficient energy investments. A fuzzy decision-making model is constructed. The paper fills the gap in performance analysis of European eco-management for environmentally friendly and efficient energy investments.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

This study aims to investigate the strategic priorities of green building projects and analyze energy consumption alternatives in green residence projects using two innovative methods.

This study uses two methods, decision-making trial and evaluation laboratory (DEMATEL) to measure strategic priorities and golden-cut quantum spherical fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) to analyze energy consumption alternatives.

The study reveals that sustainability and atmosphere are the most significant factors in determining the priorities of green residence projects, whereas innovation has a limited impact on addressing environmental challenges in the building sector. The ranking of energy use alternatives shows that sustainability issues and atmosphere quality of space heating and cooking are the top priorities, whereas other factors like white goods, water heating, lighting and space cooling are ranked lower.

This paper offers a significant contribution to the understanding of green buildings by introducing innovative methodological approaches. Theoretically, it uses the DEMATEL to enhance traditional analytical frameworks, marking a novel effort in understanding green residence projects. In addition, the golden-cut quantum spherical fuzzy TOPSIS method is introduced, offering a comprehensive decision-making framework for green projects, considering factors like energy consumption and economic feasibility. This combination of methodologies provides a holistic evaluation, emphasizing sustainability in green building construction. This study reveals untapped potential for environmental sustainability and energy efficiency, enriching the existing knowledge base.

In the era of generative artificial intelligence (AI), big data analytics, business analytics and mega global digital corporations, the profession of marketing is at a crossroads between ‘Prosumer-Marketing’ and ‘Market Grooming’. Whereas prosumer (producers + consumers) marketing means a process of exchange in which producers and consumers have equal, just, control, voluntary, fully aware engagement and control over the process of design, development and exchange of goods, services and values. On the other hand, ‘Market Grooming’ is a one-sided, unethical process of conditioning or influencing, deceiving, or persuading or manipulating and even exploiting customers by the marketing organisations, without customers' voluntary consent, permissions, awareness, etc. As the consumers have asymmetric access to information, asymmetric and lesser favourable levels of control, and lesser power in the process of exchange, as customers trust the marketers or are dependent on popular brands, the markers tend to exploit the situation. The process of market grooming has become easier due to the power of AI, generative AI, ChatGPT, TikToketing, machine learning and big data analytics leading to the development of sophisticated predictive models and persuasive models. This chapter explores and analyses a range of techniques in marketing such as permission marketing, flywheel marketing, subliminal marketing, neuromarketing, cyberstalking, ethical marketing, etc., in the era of AI. The arguments for high concerns pertaining to potential market grooming are supported by theories of ethics, theories of digital marketing and models of AI. The chapter concludes with some strategic recommendations.

This study aims to reveal whether social capital has an effect on the housing price index in Turkey, which is a developing country. The research was carried out by using the data on the basis of 81 provinces of Turkey in a 12-year period covering the years 2007–2018.

The data were subjected to panel data regression analysis and the related models were tested using the Driscoll-Kraay (1998) Estimator.

According to the results of the analysis, it was understood that there is a negative and significant relationship between social capital (SC1) and the housing price index. The results were corroborated by susceptibility testing. As the level of social capital rises in the provinces in Turkey, the manipulative and opportunistic behavior tendencies of individual and corporate house sellers decrease. These results support the principal–agent theory and theory of moral hazard, which constitute the theoretical background of the study.

No study has been found in the literature on the effect of social capital on housing prices. This situation constitutes the main motivation source of the study and shows its originality.

Although the needs and desires of customers are different, obtaining positive and negative experiences is an inevitable consequence of consuming products and services purchased by the consumer. The nature of these experiences is very important for the retail industry and in particular sports stores, as the intangible experience includes the main essence of the products and services provided by businesses; in other words, sports products are mostly experience-oriented and can be classified as an overall experience. Despite the importance of the consumer experience as a dominant and effective paradigm in consumer behaviour, the design of sports customer experience has received less attention from researchers. Therefore, the present study seeks to answer the question of what aspects of creating and developing the customer experience in sports and recreational complexes are. To answer this question, this chapter attempts to identify the areas of creating customer experiences in sports and recreational environments by examining the case of the Enghelab sports and recreational club (in Tehran, Iran) using qualitative research methods and interviewing experts in this field and using the content analysis technique. The findings indicate that cognitive, functional, comprehensive, human, physical, functional, aesthetic, sensory, social, emotional and communal components are the most important components of creating and enhancing customer experience in sports and entertainment complexes.

Therefore, the owners, managers and marketing unit of these collections should invest in the creation and development of these components in the design of their strategic marketing plans in order to provide a memorable experience for the customer during their journey and finally be able to benefit from the subsequent positive consequences such as customer satisfaction, word-of-mouth advertising, loyalty and return intention.

The purpose of the study is to examine the electricity generation potential of different renewable energy sources in Morocco, as well as to propose a novel decision support model to prioritize renewable energy alternatives. The aim is to provide recommendations that support Morocco’s energy transition strategy and assist policymakers in devising future sustainable energy policies.

The paper integrates the analytic hierarchy process with expert feedback to prioritize five renewable energy alternatives – solar photovoltaics (PV), concentrated solar panels (CSP), wind, hydro and biomass – specific to the Moroccan context. The model uses 14 sub-criteria clustered into four main categories: economic, technological, socio-political and environmental. The criteria were weighted based on inputs from local energy sector experts to capture the distinct priorities and contextual specificities of Morocco’s renewable energy landscape.

The study’s findings emphasize the dominance of economic criteria among Moroccan experts. Solar PV emerged as the most suitable option due to its cost-effectiveness and alignment with Morocco’s policies to support solar energy, followed by hydropower and wind. CSP and biomass ranked lowest due to high costs and limited viability.

This study highlighted the need for quality data to support informed decision-making, as well as for a centralized database to facilitate access to consistent information on renewable energy projects.

It is recommended that policymakers prioritize mature and cost-effective technologies by establishing supportive regulatory frameworks and expanding investments in hybrid renewable energy infrastructures.

In addition to introducing the Analytic Hierarchy Process model for the first time within the Moroccan context, to the best of the authors’ knowledge, this research draws recommendations to assist Moroccan policymakers in devising future sustainable policies for the energy sector.