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Purpose – The purpose of this study was to invent morphological North Aceh durian data as germplasm information.

Methodology – The research was conducted at Langkahan and Sawang, North Aceh Region, from March to August 2014. The material used was the durian plant that should be 20 years and preferred by the local community. Exploration as the first step of experiment was done by purposive sampling. Identification was done on the source of durian germplasm. The source of durian germplasm as the experimental object was observed for its growth and morphology. Data analysis for morphological characteristics was done by using NTSYSpc (Numerical Taxonomy and Multivariate Analysis) NTSYSpc versi 2.02.

Originality – The results showed that there were 25 accessions superior durian in Langkahan and 26 accessions superior durian in Sawang. They had different characters in the vegetative parts of the plant. The durian coefficient value of similarity in Langkahan ranged from 0.33 to 0.94, while in Sawang, it ranged from 0.24 to 0.86. The diversity of the morphological character in superior durian of Langkahan and Sawang was seen from the qualitative character (surface and color of bark, crown shape, top surface color of leaves, and leaf shape) and quantitative character (plant height, stem diameter, crown diameter, length, width, and leaf area).

Inadequate strategic planning and maintenance budget may undermine the maintenance of the Higher Education Institution Building (HEIB). Studies have shown that a customised maintenance concept such as Soft System Methodology (SSM) can improve public building maintenance operations. There is a paucity of studies regarding public HEIB maintenance in Nigeria via an SSM approach. Therefore, the research investigated the state of public HEIB and developed a framework to improve public HEIB maintenance practices in Nigeria.

The research adopted SSM to understand Nigeria’s public HEIB maintenance practices. The SSM permitted a substitute approach to improve public HEIB maintenance practices via a developed framework. Data were collated via virtual interviews with experts, and findings were presented in line with the SSM seven steps.

Findings show that besides the shoddy state of public HEIB maintenance, there is no public digitalised HEIB framework to improve maintenance practices across Nigeria’s higher education institutions. The study developed a digitalised framework with the support of Computerised Maintenance Management System from the findings. It would reposition the public HEIB and stir up various agencies/departments/units managing maintenance for better service delivery via integrated delivery, practical, methodological and managerial aspects.

The research investigated Nigeria’s public HEIB maintenance practices via SSM to identify the required document and propose a feasible framework to improve Nigeria’s HEIB maintenance practices. Besides the developed conceptual framework, Nigeria’s HEIB maintenance practitioners and higher institution chief executives can use the recommended framework as guidelines to improve HEIB maintenance practices.

The purpose of this paper is to propose a model that will demonstrate how the integration of Salam (exclusive agricultural commodity trade) with Takaful (micro-Takaful – a subdivision of Islamic insurance) and value chain can address major challenges facing the agricultural sector in Kano State, Nigeria.

The study conducted a thorough and critical analysis of relevant literature and existing models of financing agriculture in Nigeria to come up with the proposed model.

The findings indicate that measures undertaken to address the major challenges fail. In view of this, this study proposed Bay-Salam with Takaful and value chain model to solve a number of challenges such as poor access to financing, poor marketing and pricing, delay, collateral requirement and risk issues in order to avail farmers with easy access to finance and provide effective security to financial institutions.

The paper is limited to using secondary data. Therefore, empirical investigation can be carried out to strengthen the validation of the model.

The study outcome seeks to improve the productivity of the farmers through enhancing their access to finance. This will increase their level of production and provide more employment opportunities. In addition, it will boost financial inclusion, income generation, poverty alleviation, standard of living, food security and overall economic growth and development.

The novelty of this study lies in the integration of classical Bay-Salam with Takaful and value chain and create a unique model structure which the researchers do not come across in any research that presented it in Nigeria.

The aim of the study was to determine the region brand’s strength by measuring the awareness of the regional brand elements, associations and the perception of the region’s promotional activity in the corporate customers’ group.

To obtain the necessary data, this study conducted computer-assisted web interviewing on a sample of 151 small and medium-sized enterprises (SMEs) registered in the Mazowieckie Voivodeship and engaged in furniture production and food and beverage production. Statistical data analysis included Pearson and Spearman’s rank correlation and chi-square tests.

The survey showed a high number of brand associations with the region of Mazovia, but the level of brand recognition was low. The awareness of the region’s logo among SMEs shows the strongest correlation with the belief that promotional activities increased the scope of company operations. Moreover, this evidences the perceived utility of the brand among those customers.

The regional authorities should invest more in the frequency of promoting the region among certain strongly engaged user groups to increase their brand awareness level. Furthermore, local authorities should try establishing an umbrella brand that would cover several sub-brands promoting separate industries in the region.

To the best of the authors’ knowledge, this is the first study in Poland that focused on regional branding effects among entrepreneurs and using a quantitative method. The relationship between the studied entrepreneurs’ willingness to use the Mazovia brand and their range of operations indicates that some enterprises already enjoy greater trust thanks to the brand, which increases their loyalty toward the region.

The purpose of this paper is to determine patient expectation and perception of pharmaceutical care services in order to measure the level of patient satisfaction provided by Indonesia’s health coverage (IHC) system.

A patient satisfaction survey was conducted at primary-level and secondary-level health facilities operating under IHC system. The assessment was performed using a closed-ended questionnaire that had been tested for validity and reliability. The patients’ point of view was evaluated based on their expectation and perception of six dimensions of the pharmaceutical care services they had received. Patient satisfaction was calculated based on the gap between their expectation and their perception.

A total of 602 patients participated in this research. The levels of the patients’ expectation of the pharmaceutical care services provided at primary-level health facilities range from high (3.39) to very high (3.54), whereas at secondary-level health facilities, the range was from low (2.04) to very high (3.75). This indicates that patients have a higher expectation of the provided pharmaceutical care services compared to the actual experience of the healthcare services that they received, resulting in a low value in the measurement of patient satisfaction levels.

The high level of patient expectation is an opportunity for pharmacists at both primary-level and secondary-level health facilities to continue developing pharmaceutical care services. Improving drug information service, patient counseling and reducing patient waiting time can be good ways to increase patient satisfaction within pharmaceutical care services.

This study aims to examine the three dimensions of market orientation, namely, customer orientation, competitor orientation and inter-function coordination, which influence the accountability in the financial and social performance of tourism operators in large touristic cities.

In total, 95 usable questionnaires as the required data were collected from the top managers of four- and five-star hotels in Iran.

Partial least squares (PLS) results confirm that customer orientation and inter-function coordination influence both the financial and social performance of the hospitality sector yet reveal that competitor orientation has no significant relationship with social performance.

These findings not only highlight the compatibility of PLS with various forms of statistical analyzes but also furthers the current understanding of hospitality networks in megacity economies, where literature are scarce.

The findings of this study can help policymakers, tourism associations and practitioners enhance the accountability and sustainable financial and social performance of the hospitality industry in megacities. This study proposes some unique measurements for the social and financial performance of the hospitality sectors.

The paper states some new measurements for the social performance of the hospitality sectors. In addition, measuring the impacts of market orientation on the financial and social aspects of hotels is totally unique.

As the tourism industry becomes more vital for the success of many economies around the world, the importance of technology in tourism grows daily. Alongside increasing tourism importance and popularity, the amount of significant data grows, too. On daily basis, millions of people write their opinions, suggestions and views about accommodation, services, and much more on various websites. Well-processed and filtered data can provide a lot of useful information that can be used for making tourists' experiences much better and help us decide when selecting a hotel or a restaurant. Thus, the purpose of this study is to explore machine and deep learning models for predicting sentiment and rating from tourist reviews.

This paper used machine learning models such as Naïve Bayes, support vector machines (SVM), convolutional neural network (CNN), long short-term memory (LSTM) and bidirectional long short-term memory (BiLSTM) for extracting sentiment and ratings from tourist reviews. These models were trained to classify reviews into positive, negative, or neutral sentiment, and into one to five grades or stars. Data used for training the models were gathered from TripAdvisor, the world's largest travel platform. The models based on multinomial Naïve Bayes (MNB) and SVM were trained using the term frequency-inverse document frequency (TF-IDF) for word representations while deep learning models were trained using global vectors (GloVe) for word representation. The results from testing these models are presented, compared and discussed.

The performance of machine and learning models achieved high accuracy in predicting positive, negative, or neutral sentiments and ratings from tourist reviews. The optimal model architecture for both classification tasks was a deep learning model based on BiLSTM. The study’s results confirmed that deep learning models are more efficient and accurate than machine learning algorithms.

The proposed models allow for forecasting the number of tourist arrivals and expenditure, gaining insights into the tourists' profiles, improving overall customer experience, and upgrading marketing strategies. Different service sectors can use the implemented models to get insights into customer satisfaction with the products and services as well as to predict the opinions given a particular context.

This study developed and compared different machine learning models for classifying customer reviews as positive, negative, or neutral, as well as predicting ratings with one to five stars based on a TripAdvisor hotel reviews dataset that contains 20,491 unique hotel reviews.

This research aims to investigate the factors that can influence Bumiputera contractors’ acceptance of the Contractor’s All Risks (CAR) takāful (Islamic insurance) product using the theory of reasoned action (TRA).

Using the method of quantitative surveys, 414 questionnaires were collected from targeted Bumiputera contractors in Malaysia (grade G1 to grade G7), except in Sabah and Sarawak, that are registered with the Construction Industry Development Board (CIDB) and are also members of Persatuan Kontraktor Melayu Malaysia (PKMM). The data was analysed using the partial least squares structural equation modeling (PLS-SEM) technique.

The findings from the PLS-SEM analysis show that attitude, subjective norm, religiosity and awareness have a positive relationship with Bumiputera contractors’ acceptance of the CAR takāful product. Religiosity appeared to be the most significant factor influencing Bumiputera contractors’ acceptance of the CAR takāful product.

The respondents in this study only comprised Bumiputera contractors in Peninsular Malaysia, excluding those from Sabah and Sarawak. Therefore, it is not possible to generalise the findings to a broader population.

Takāful operators and their sales and marketing departments need to act proactively in promoting the benefits of investing in CAR takāful that follows Sharīʾah (Islamic law) rules and principles. They should create mechanisms to market CAR takāful better, thus accelerating its acceptance rate among contractors.

The paper uses the proposed extended TRA model, which includes the variables of religiosity and awareness in the TRA model. These variables were successfully integrated in the model, and the findings show that they have significantly contributed to the acceptance of the CAR takāful product among Bumiputera contractors.