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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.

Health technologies are an issue that directly affects the sustainability and quality of health services. Due to budget constraints, it is not financially possible for businesses to apply comprehensive improvement strategies to all these criteria. In this case, it is possible for businesses to implement more priority strategies. Accordingly, the main purpose of this study is to evaluate the important performance indicators of health technology investments.

Firstly, with the help of the artificial intelligence system, a decision matrix is established. Secondly, spherical fuzzy total order of preference decision-making trial and evaluation laboratory methodology is taken into consideration for weighting the criteria. Thirdly, emerging seven countries are ranked by using spherical fuzzy MultiAtributive Ideal-Real Comparative Analysis (MAIRCA).

The findings demonstrate that the criteria of health policies and research and development are defined as the most significant factor in this regard. China and Turkey are also found to be the most successful emerging countries with respect to the performance of health technology investments.

The main contribution of this study is that a novel decision-making model is generated by integrating artificial methodology into the spherical fuzzy sets.

This study aims to explore the antecedent factors that directly and indirectly influence electronic word of mouth (eWoM) for social commerce (s-commerce) in two developing countries (e.g. Kuwait and the United Arab Emirates [UAE]) by extending social cognitive theory.

This study uses a previous robust model (Rouibah et al., 2021) as theoretical background to investigate and compares the antecedents (trust in Instagram, perceived risks) on eWoM for s-commerce through the mediation of three mediators (perceived enjoyment, perceived value and customer satisfaction) among two Arab countries. Data was collected from Kuwait (n = 1,132) and the UAE (n = 190). Different statistical analyses and structured equation modeling-based analysis of moment structure are used to test the robustness of the research model.

This study found customer satisfaction to be most important factor that mediates the effect independent factors on eWoM for s-commerce in both countries. Surprisingly, perceived enjoyment has no effect, and trust in Instagram and perceived risks are the most important factors that are considered imperative for customer satisfaction and positive feedback.

One limitation of this study is that the author does not focus on the difference between the effects of textual and graphical information on customers’ decisions and trust in buying merchandise. Another limitation is that this study focuses on Kuwait and the UAE. Other Gulf Cooperation Council countries are also growing exponentially, and mobile and internet penetration rates are booming; they could be a trigger for more studies on whether differences occur among all of them.

The first implication is that it is the first in its field to extend the effects of eWoM. To the best of the author’s knowledge, compared to the online research this study is unique because the authors examine six factors for eWoM in s-commerce using the Instagram platform as opposed to other platforms.

The third implication of this study is that the previous ones have applied eWoM to different subjects of e-commerce such as tourism and marketing but have concentrated less on s-commerce, where in-depth research is needed much more to explore factors and theories that explain human behavior.

Furthermore, most of these studies have focused on the intention to use (Dincer and Dincer, 2023; X. Hu, Chen, Davison, and Liu, 2022; Zhou et al., 2023). However, the attention in this research is on the actual use.

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.

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.

There is a compelling need for developing constructs in management science rather than adapting the constructs that have been developed in other domains. Having emerged in the 1950s, quality of work-life (QWL) measures have proved to be ineffective due to the lack of conceptual clarity and theoretical support. The article analyses the QWL measures highlights their coherence and verifies them for being used in specific contexts.

The study includes three stages to develop a QWL Measurement Scale. Fourteen questions were developed based on QWL concepts. They were validated using exploratory factor analysis (EFA) which split the dimensions into five factors. A survey was conducted on 375 medical residents. Finally, confirmatory factor analysis (CFA), convergence and validity were tested along the five dimensions.

Results extend the QWL concept and provide theoretical support for the same. Five dimensions were developed to measure QWL namely: pay and benefits, supervision, intra-group relations, working conditions and training.

The study may offer an overview of evaluation strategies to researchers and organizations that aim to improve employee QWL while they enhance its effectiveness through reliable instruments.

The scale developed in this study contributes to the body of QWL literature in the healthcare arena. It may be beneficial to carry out further research in this domain.

This research article aims to systematically explore the association between digitalisation and individual investors’ behavioural biases. Through an extensive exploration of digitalisation modes and their various serviceable avenues in the investment arena, the study aims to elucidate the impact of behavioural biases on individual investors’ investment decision-making processes.

The study employs Interpretative Phenomenological Analysis (IPA) to gain insights into behavioural finance and the associated behavioural biases of investors in digitalisation. IPA, a qualitative method grounded in heuristic, phenomenological, and idiographic elements, facilitates the exploration of individual investor experiences and the role of digitalisation and behavioural biases within.

Investors are categorised into two groups – decision seekers and decision makers – based on their digital inclination and the purpose behind using digital tools. The attributes of these segments are detailed under the sub-themes of Digital Inclination, Market Cognizance, Sophistication and Maturity, Sophomorism and Perception of Digitalisation. The study also identifies the specific behavioural biases pertinent to each segment. Additionally, it introduces a novel section on the insights related to human emotions, behaviour and sentiment within financial markets.

The essence of the current article is the application of the IPA method to the field of behavioural finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive understanding of both, digitalisation and behavioural biases that affect the individual investor’s decision-making. It offers valuable insights for researchers, academicians and scholars in behavioural finance, enhancing the understanding of how behavioural biases influence investment decisions.