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Smart banking services (SBS) are critical for developing countries to achieve developmental goals. The success of SBS is dependent on the considerable perceived customer experience of provided services. Based on technology adoption studies, this study aims to model smart customer experience (SCE) outcomes by investigating the relationships between SCE, customer gratitude, continuance intentions and positive word-of-mouth (P-WOM).

The current research included 384 bank clients as participants. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

According to the findings, SCE directly increases customer gratitude, continuance intention to adopt smart services and P-WOM. Customer gratitude enhances continuance intentions and P-WOM. Additionally, customer gratitude mediates the relationship between SCE, continuance intention and P-WOM. Finally, the findings revealed that customer innovativeness and optimism play a substantial moderating impact among the variables studied.

This is the first research to include all of these variables. Furthermore, to the best of the authors' knowledge, this is the first empirical study of these linkages in the banking sector of emerging nations.

This paper aims at discovering the traditional techniques of Persian architecture for covering large-span spaces with a kind of ribbed vault titled “Karbandi”. This structure is generated by intersecting several arches with a harmonic stellar geometry. Preliminary studies show that span factor affects the structural form of karbandi and large-span cases, despite similar architectural forms, have different structural systems and specific construction methods. The main focus of this paper is how karbandi has been designed and built on large-spans. To answer this question, the configuration and construction of a large-span karbandi in Tabriz Bazaar were recognized.

Data collection of the research was initially done in three parallel directions through the archival study of restoration documents, direct observation of the corpus of the vaultings and interviews with the master mason of the Haj-Mohammad-Qoli Timche restoration team. Then by cross-referencing the gathered data, the construction process of the karbandi was simulated in Rhino 6 and Grasshoppers software and its BIM-M models were created in three levels of development: LOD300, LOD350 and LOD400. In the next step, the preliminary BIM-M models of the karbandi were presented to the interviewed mason and revised and completed based on his comments.

Analyzing the BIM models by reverse engineering, resulted in (1) Discovering a unique self-supporting masonry construction method applied for the erection of karbandi vaulting on large-spans. (2) Finding the effect of scale factor on the architectural and structural form of the karbandi vault. (3) Discovering the connection types of the karbandi vault based on the construction details.

Despite the wide applications of karbandi vaults throughout history, very little information of their construction techniques is available. The techniques have mostly been experientially and orally passed down from masters to apprentices and rarely been documented. The quest to design and construct a karbandi vault is therefore like solving a puzzle whose most important guide is historical cases. Due to the geometric complexity of karbandi and its ability to cover large-span spaces, solving the puzzle can lead to achieving some technical ideas for masonry cross-ribbed vaulting. A great riddle of the karbandi vaults is how to design and build them on a large span.

Records are current documents containing crucial personal, legal, financial and medical information, while archives house non-current documents with the same details. This study specifically aims to measure existing research in records and archives management with various scientific indicators.

Data extraction was conducted using the Web of Science, resulting in a data set of 2003 records for further analysis. Biblioshiny and VOSviewer have been used for mapping and visualization of the extracted data.

Managing and organizing this essential information is equally vital to maintaining records and archives. The findings encompass various aspects such as publications and citations, influential authors, source impact factors, relevant articles, affiliations, co-authorship trends across the top 10 countries and regions, references, publication year spectroscopy, keyword co-occurrence and historiography. The study concludes that medical records management prominently dominates the selected research area.

The study reflects the advancements in management systems and continues to emerge as research on the management of records and archives has gained significance.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

This paper aims to identify potential avenues for innovation in urban hotel management by analyzing self-reported data from visitors regarding their experience with interior design.

A qualitative exploratory computer-assisted content analysis was conducted to identify the impact of interior design on the guest experience. Leximancer 4.0 software analyzed 2,562 reviews from urban hotels collected through a reservation website.

The findings reveal that data reported by guests on interior design play a crucial role in shaping guest experiences, both positively and negatively. The esthetic appeal of interior design is shown to impact resting and comfort, affecting overall performance significantly. The study also highlights how different star categories of hotels and variations in visitors' purposes for their stay lead to distinct guest experiences and different opportunities to innovate.

The study’s results provide evidence for researchers and practitioners of the potential of the guest-reported interior design experience as a valuable source for fostering innovation. In addition, in the hotel industry, innovation may eventually be attained through interior design renovation.

Self-reported data from guests on interior design is an effective tool for innovation. Making interior design a priority throughout the establishment and ongoing management of a hotel is crucial. By integrating interior design, not only can potential negative experiences be avoided, but greater guest satisfaction can also be achieved during their stay, promoting memorable experiences that align with the hotel category and customer expectations.

This research emphasizes the importance of interior design as a catalyst for innovation and improved social experiences in the hospitality industry. Innovation in interior design can improve hotel performance in several dimensions, including attracting more visitors to the hotel and the area, increasing tourism revenue for local businesses and contributing to the broader societal goal of reducing environmental impact and promoting sustainability.

This article adopts a guest-centered methodology to provide valuable insights for hotel managers to leverage interior design as a tool for innovation in the hospitality industry after showing that interior design enhances guests' experiences, comfort and hotel differentiation.

This study aims to investigate whether the presence of women in the boardroom influences companies’ environmental, social and governance (ESG) performance. Furthermore, it examines whether the COVID-19 pandemic and family control affect the relationship.

This study uses nonfinancial firms listed on the Indonesia and Malaysia Stock Exchange during 2018-2021. Thomson Reuters’ database is used to collect the ESG scores. Using 312 firm-year observations, the authors apply multiple regressions and sensitivity testing to ensure the robustness of the results.

This study provides empirical evidence that the presence of women in the boardroom improves companies’ ESG and family control weakens the relationship. Meanwhile, there is no support on the moderating effect of the COVID-19 pandemic. The authors also conducted additional tests using ESG pillars (i.e. environment, social and governance pillars) as the dependent variable. The findings are robust to alternative samplings.

This research is limited to Indonesia and Malaysia, thus affecting the generalizability of the results to all developing countries. The sample size is relatively small due to data limitations related to the availability of ESG scores.

The findings of this study provide a basis for the government to establish mandatory regulations regarding sustainability performance. The positive relationship between women on boards and better ESG performance suggests that encouraging gender diversity in corporate leadership can improve sustainability practices. The government may consider implementing gender quota regulations to increase women's representation on corporate boards.

Shareholders can pursue investment portfolios in socially responsible companies, prioritizing ESG performance. In addition, investors should consider the presence of women in the company’s boardroom and whether family control exists when making investment decisions.

Overall, the originality and significance of this research lie in its comprehensive examination of the moderating factors, the inclusion of different governance systems in the sample, and the exploration of psychological aspects, contributing to a deeper and more nuanced understanding of the relationship between women on boards and ESG performance in the context of developing countries.

Agricultural waste and food sources are some of the pollutants of the environment. One of these wastes is the peel of fruits that cannot be consumed as food. In this regard, walnut husk (WH) and oleaster peel (PO) are known as two important sources of tannin and are bulky wastes. Because of the high percentage of tannin, these materials can be used as a natural source for the preparation of bio-mordant in the dyeing process.

In this study, Reseda and Madder were used as natural dyes in the presence of a mixture of two bio-mordants. WH and PO were selected as bio-mordant. All natural resources are extracted to obtain the juice. The phenolic percentage of tannin-containing extracts was evaluated and then it was used for wool yarns by premordanting method. The results of evaluating the fastness properties using the ISO method.

The most important achievement of this research is the use of agricultural waste in the dyeing process to reduce environmental pollution and create added value. All compounds rich in tannin have some phenolic components, therefore the amount of phenolic content of these extracts was evaluated. The effect of mixing the mordant on the color characteristics of the yarns was investigated and the results showed that changing the ratio of the combination of two mordant is effective on the K/S values. The results of evaluating the fastness properties using the ISO method showed that the washing, rubbing and light fastness in the presence of mordant is good, good and moderate, respectively.

In this paper, to the best of the authors’ knowledge, for the first time, the combination of two natural extracts obtained from agricultural waste has been used to create a new bio-mordant on fibers and improve stability.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.

A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.

The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.

It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.

Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.

The aim of this paper is to review and categorise the body of existing research in order to better understand the state of food tourism. The primary objective of this study is to identify emerging themes in the area of food tourism and to highlight the relationships among them.

This research consists of a systematic literature review of academic articles from the Scopus and Web of Science databases.

Ten themes of Food Tourism emerged from the analysis, i.e. Food Tourism and Local Food, Food Tourism and Sustainability, Food Tourism and Economy, Food Tourism and Food waste management, Food Tourism and Culture, Food Tourism and Environment, Food Tourism and Information Technology, Food Tourism and COVID-19, Food Tourism and Post pandemic consumer trust and Food Tourism and Tourism and Hospitality sector.

This study elaborates on the theoretical pieces of evidence on the connection between food and tourism. Not only limited to food tourism, but this paper also contributes to the literature in the area of economy, sustainability, post-COVID-19, food waste management, environment and technological innovations in food tourism.

This study contributes to a deeper understanding of the topic at hand. The study begins by systematically examining the topic to offer a thorough and in-depth analysis of food tourism. There is not a single study which has covered these many themes of food tourism, which makes it an important contribution to the literature.