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Assessing anthropomorphic tendency in relation to real estate purchase decisions and analysing the elements of friendliness, aggressiveness, pleasure and arousal as a link to the spatial memory of the consumer. This study aims to help brands and advertisers in the real estate industry to create meaningful consumer relationships by using elements that are associated with positive spatial experience. By formulating a detailed questionnaire with adapted variables from proven research and a multilayered approach of theoretic and practical analysis, this paper situates the identified variables in the plane of space and customer experience.

By using structural equation modeling, this study analyses a sample data of 411 consumers and their response to elements of housing.

The findings of this study showed that variables of friendliness, aggressiveness, pleasure and arousal significantly impact consumer’s real estate purchase decision; however, anthropomorphic tendency does not have a significant impact. Through theoretical analysis, it was found that spatial memory may have a role in the visual and display of the variables.

The merit of this paper lies in the discussion it has raised with regard to the intersection between theoretics of space and the chosen variables. In the field of business and management, often philosophical implications of spatiality may not be actively associated with numerical computation. This paper not only looks at brand anthropomorphism’s impact on real estate purchase decisions but also looks at friendliness and other mentioned variables as significantly impacting purchase decisions and linked to memory, space and affiliation.

The main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.

The design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.

The modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.

Business limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.

The modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.

The adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.

Acknowledging previous scholarly focus on functional attributes in understanding technology acceptance behaviour, the current study aims to offer a novel perspective by integrating eight different dimensions of utilitarian and hedonic attributes to examine their influence in delivering a holistic web-based retail shopping experience.

The research model was tested and validated through data collected from 370 online shoppers across both hedonic and utilitarian product ranges. Hypotheses were tested using covariance-based structural equation modelling with multi-group analysis to examine the moderation effect.

The findings strongly support the model confirming eight new utilitarian and hedonic dimensions that influence web-based retail shopping behaviour. The findings also confirm that hedonic attributes remain important even for utilitarian product purchasing.

The key managerial implication is the demonstrated need to balance utilitarian and hedonic attributes in web-based retail platforms, where previously, there has been an overemphasis on functional features. Web-based retailers should consider the optimal blend of utilitarian (e.g. information quality) and hedonic (e.g. aesthetic) attributes in the design of a retail shopping site, irrespective of the product category.

This study integrates multiple dimensions of utilitarian and hedonic attributes into a single model and highlights the interplay of these attributes, thus extending the technology acceptance model. This paper also advances scholarship through its identification of attribute impact across different product categories.

Visual sustainability has gained significant relevance for both firms and consumers. While the importance of perceived sustainability in package design is well researched, there is a research gap regarding divergent responses of consumers to perceived visual sustainability. This research aims to close this gap by providing deeper insights into the underlying mechanisms of perceived visual sustainability in package design. As a boundary condition, this work also investigates gender differences in response to a design’s visual sustainability.

To explore the mediating influences of cognitive (i.e. a product’s gentleness and power) versus emotional (i.e. moral satisfaction) attributes as well as the role of consumer gender in the perceived visual sustainability–purchase intention relationship, the authors extend previous research through three experiments.

Study 1 provides initial evidence supporting the main effect of perceived visual sustainability on purchase intention. Findings of Study 2 show that moral satisfaction serves as a significant driver of purchase intention for females, while power-related attributes are more influential for males. Study 3 provides additional evidence for the main effect, the interaction effect with consumer gender and underlying mechanisms.

These findings have important implications for marketers and designers aiming to design packages that appeal to different consumer groups based on their (gender-specific) values regarding visual sustainability.

This work extends the literature on green behavior by highlighting the importance of perceived visual sustainability as a factor that influences purchase intention and the role of cognitive versus affective mechanisms in shaping consumer responses to design sustainability.

This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods.

The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis.

In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods.

Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers.

Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer’s experience.

Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies.

We review and synthesize the existing research on directors' and officers’ (D&O) liability insurance. Our objectives are (1) to examine the institutional forces and regulatory requirements that have influenced the development of D&O liability insurance; (2) to identify the factors that influence firms to purchase D&O liability insurance and explore the consequences associated with its usage and (3) to identify gaps in the current literature and provide recommendations for future research on D&O liability insurance.

We perform a systematic literature review (SLR) using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies that investigate the determinants and consequences of D&O liability insurance. Using a Boolean search strategy on the “Web of Science” (WoS) and PRISMA selection criteria, we review 64 published archival research articles and three working papers from 1987 to October 2023.

Our review reveals that disclosing detailed information regarding D&O liability insurance, such as total insurance premiums and coverage limit, is predominantly voluntary, except in Taiwan. Our findings suggest that the decision to purchase D&O liability insurance is influenced by litigation risk, which is determined by factors such as firm size, complexity and corporate governance variables. We also find that D&O liability insurance has implications for financial reporting, audit outcomes, investment behavior and capital market performance.

In the post-COVID era, where firms face pressure due to financial constraints, our research emphasizes the practical importance of carefully considering and understanding the impact of D&O liability insurance, particularly as it concerns the demand for such insurance.

To the best of our knowledge, this study represents the first systematic review of previous research on D&O liability insurance. Our review highlights some research gaps, particularly in relation to the implications for financial reporting practices, auditing outcomes, firm investment behavior and capital market consequences.

This research aimed to raise awareness about the need for safety measures and features of online food delivery applications (OFDAs) to build electronic trust (e-trust) with augmented purchase intention among customers. Moreover, this study explores the attributes of electronic commerce (e-commerce) and how e-trust influences the purchasing intention of consumers while ordering food through OFDAs including fear of contagious diseases. Determinants of e-commerce in the digital era profoundly impact the performance of enterprises.

Data from 493 food consumers collected from Federal Capital Territory (FCT) Pakistan, who were regular users of OFDAs. To scrutinize the dataset, confirmatory factor analysis (CFA) was conducted to assess the construct validity in this research study. Structural equation modeling (SEM), which is facilitated by Smart-PLS, was employed to examine the direct, moderation and mediation effects of the proposed model.

Results revealed the positive and significant impact of the e-trust on the purchase intention. Additionally, e-trust acted as a mediating factor in the connection between electronic security (e-security), electronic privacy (e-privacy), usability, electronic payment (e-payment), electronic innovativeness (e-innovativeness) and the buyer's purchase intention. Furthermore, the fear of contagious viruses negatively moderated the e-trust and purchase intention that weakened buying behavior.

This research is primarily centered on enhancing the comprehension regarding safety orientation within the context of an evolving restaurant industry. The findings of this study hold substantial contributions for academics, web developers, application designers, OFDAs, restaurants and other businesses since they indicate the attractiveness of OFDAs in generating feelings of pleasure and boosting users' intentions to keep using the application.

The rise of artificial intelligence (AI) and machine learning has largely promoted the emergence of “autonomous decision-making” (ADM). This paper aims to establish a personalized artificial intelligent housekeeper (AIH) that knows more about our hobbies, habits, personality traits, and shopping needs than ourselves and can replace us to do some habitual purchasing behavior.

We propose an AI decision-making method based on machine learning algorithm, a novel framework for personalized customer preference and purchase. First, the method uses interactive big data to predict a potential consumer’s decision possibility. Then, the method mines the correlation between consumer decision possibility and various factors affecting consumer behavior. Finally, the machine learning algorithm is used to estimate the consumer’s purchase decision according to the comprehensive influencing factors data of the target consumer.

The experimental results show that the method can predict the regular consumption behavior of consumers in advance and make accurate decision-making behavior. It can find correlations from a large amount of data to help predict many simple purchase decisions in our life, and become our AIH.

This study introduces a new approach that not only has the auxiliary decision-making function but also has the decision-making function. These findings contribute to the research on automated decision-making process of AI and on human–technology interaction by investigating how data attributes consumer purchase decision to AI.

Blogs are websites that contain posts about a wide range of topics, often written by fashion enthusiasts referred to as bloggers. With the increasing prevalence and popularity of digital media and social media, fashion bloggers help to attract business and influence and engage various stakeholders, especially customers. The present exploratory study provided valuable insights regarding fashion consumption, preference, and buying behavior of young women consumers of metropolitan cities of India like Delhi, Hyderabad, Bangalore, Pune, and Mumbai. The study was conducted under the domain of exploratory study. Snowball and Purposive random sampling techniques were employed to identify and reach respondents of both categories – women consumers and bloggers. A conscious attempt was made to include women from different demographics such as age, marital status, income, area of residence, employment status, etc. Primary data were collected with the help of questionnaires. The findings of the research revealed bloggers through their blogs are the new trendsetters and influence fashion adoption, especially by the young social media savvy consumers. Their blogs impact public perceptions of fashion and sometimes are precursors of new fashion trends. The findings of the study interestingly brought forth the fact that millennial women buying decision is significantly influenced by fashion blogs for the purchase of clothing and accessories. The findings also clearly indicated that blogs significantly influenced respondents’ attitude toward the purchase of branded merchandise. Fashion bloggers besides providing information and inspiration to the blog readers, also at times assist and/or give consultation to their followers.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.