Search results

Improving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions.

Rice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences.

Ugandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya.

The study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples.

Data has become a factor of production. This occurs when history enters the era of big data, in which technologies such as artificial intelligence, cloud computing and blockchain are used to collect, manipulate, mine and process data. Data is a special product of labor, a sub-derivative of other production factors.

The data factor has a dual attribute: being physical (technical) and social. The social attribute of the data factor can not only materialize the technical attribute but also amplify it. In other words, the data has a multiplication effect on the allocation efficiency of other production factors. The social attribute of the data is brought out via the technical attribute as the medium. From a technical perspective, this medium is strongly adhesive, and after being bonded with other factors of production, it will only lead to a physical reaction and not change the nature of other factors.

However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

Therefore, to get a scientific understanding of the dual attribute and its interaction effects on the data factor, it is necessary to take the following steps. We should promote institutional design that amplifies the positive externality, with a focus on facilitating public data sharing and improving the value of commercial data development. Also, we need to strengthen institutional arrangements that prevent and control the negative externality by emphasizing data supervision based on data types and levels as well as the rule of law.

This study aims to gain a first explorative view on what intrinsic/extrinsic attributes a generic cup for hot beverage should possess to be perceived as eco-friendly, and how some attributes of a hot beverage could influence consumers’ purchase decision and willingness to pay (WTP) for that beverage dispensed by vending machines (VMs).

A questionnaire was developed in 2021 and sent to all students of an Italian university campus. For the first goal, students were asked to assign a score to some eco-friendly intrinsic/extrinsic attributes using a five-point Likert scale. For the second aim, a choice experiment with six scenarios was developed.

Both intrinsic and extrinsic attributes play a key role in shaping students’ opinions and preferences. Results indicate that students are attracted by the idea of a cup that communicates its environmental properties through corresponding labels and information, and it is made by materials that guarantee biodegradability, recyclability or reusability.

The research represents the first academic attempt to provide a first consumers’ viewpoint on the importance of eco-friendly attributes of cups for hot beverages able to influence consumers’ perceptions and consumption choices of hot beverages dispensed by VMs.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

Medical research requires biological material and data collected through biobanks in reliable processes with quality assurance. Medical studies based on data with unknown or questionable quality are useless or even dangerous, as evidenced by recent examples of withdrawn studies. Medical data sets consist of highly sensitive personal data, which has to be protected carefully and is available for research only after the approval of ethics committees. The purpose of this research is to propose an architecture to support researchers to efficiently and effectively identify relevant collections of material and data with documented quality for their research projects while observing strict privacy rules.

Following a design science approach, this paper develops a conceptual model for capturing and relating metadata of medical data in biobanks to support medical research.

This study describes the landscape of biobanks as federated medical data lakes such as the collections of samples and their annotations in the European federation of biobanks (Biobanking and Biomolecular Resources Research Infrastructure – European Research Infrastructure Consortium, BBMRI-ERIC) and develops a conceptual model capturing schema information with quality annotation. This paper discusses the quality dimensions for data sets for medical research in-depth and proposes representations of both the metadata and data quality documentation with the aim to support researchers to effectively and efficiently identify suitable data sets for medical studies.

This novel conceptual model for metadata for medical data lakes has a unique focus on the high privacy requirements of the data sets contained in medical data lakes and also stands out in the detailed representation of data quality and metadata quality of medical data sets.

Ecologically habitat is an area of a particular species wherefrom its play every relationship with the surrounding. Therefore, every species hold habitat that supports to survive its life. The large terrestrial herbivore animal elephant (Elephas maximus) requires deferent kind of habitat for their biological behaviour. Forest habitat one of the landscapes entire their home range is very much responsible for selecting suitable habitat. The nature of habitat selection by an elephant is deeply concerned with landscape attributes.

The present study started in this opinion. The study area Panchet Forest Division (PFD) has 28 forest patches are not in same size. Generally, forest patches are the most suitable habitat for elephant in every forest landscape as well as in PFD. But which forest patch will be highly suitable that depends on ecological function of other geospatial attributes like patch shape complexity, patch core, road intervention intensity, amount of water body and composition of the forest. The present study measures these attributes by different sequential steps such as field inquiry, satellite image processing and GIS application by using ERDAS 9.3 and ArcGIS 10.3 version software.

After measuring these attributes value, Habitat Suitability Index is assessed through combined weighted principle method and prepared a suitability map. This map signifies that Joypur-I and II, Upper Peardoba, Brindabanpur, Kalabagan forest patches have good condition for elephant to prefer as a suitable habitat in PFD.

Spatial classification of elephant habitat in PFD helps society and managing authority. It facilitates better management and reducing the chance of human – elephant frequent contact.

This study is an attempt to apply the techniques of semiotics in conjunction with quantitative analysis to decode and interpret an advertisement which promotes the South Australian Barossa Valley as a tourist destination.

A survey was submitted to a Southeast Asian student and postgraduate sample. Regression analysis and qualitative analysis were carried out, which suggested that the advertisement was engaging the majority of the audience.

Most respondents expressed a desire to visit the location and used language which was evocative and connective. Those who did not or who were turned off by the advertisement's content expressed themselves in language which terminated further engagement.

The sample was a non-target group, but this is an advantage because it provides a base level of unconditioned response.

A better understanding of semiotics may reinforce other areas of marketing endeavour such as social marketing approaches which are gaining more importance in the still developing COVID-19 economy. This methodology can be extended to other marketing communication contexts.

Once campaigns have been aimed at target audiences, there may be potential to orientate another campaign at non-target audiences using the same advertisement. In terms of global marketing, this is extension rather than adaptation.

This study provides an example of how marketing could use semiotics in conjunction with quantitative methods to determine an audience's response and the intention to purchase a product or service.

Studying the gap between improvements in operational performance of a manufacturing organization does not necessarily represent the existent of safe and healthy work. The purpose of this paper is to fill this gap validating a scale about social practices.

The literature was studied; data analysis instrument and the scale validated by Q-sort. The reliability and validity of research instrument indicators were drawing from the analysis of judges. The data were assessed by convergence matrix.

It was validated five social practices factors. It was enabled the adequacy of the name of the constructs and establishment which indicators better convergence to the constructs.

The judge´s number that answered the research was low. The level of convergence related of two factors was above 50 percent.

It is possible to achieve better levels of performance through social practices. Organizations must rethink the management and the routine of the workers to implement the operational practices.

The practices need to have with well-defined rules, as well as action to drive compliance. This vision also needs to be expanded to suppliers, customers and society.

Highlight five points: technology is the main factor for analyzes and decisions; the search for quality leads organizations to seek practices that improve workers’ well-being, health and safety; the activities of the worker are carried out on the factory, or in the work environment; Should not to belittle the local community; culture is an essential factor to continuous improvement.

After the COVID-19 outbreak began, travel demand dropped sharply and the potential impact of COVID-19 on sharing accommodations appears to be significant. Thus, it would be meaningful to investigate how travelers have changed their perceptions of staying at sharing accommodations in the wake of the coronavirus pandemic. The purpose of this research was to compare consumers' perceived risks of using sharing accommodations, such as Airbnb, before and during the coronavirus pandemic.

Paired sample t-tests were applied, using two surveys collected in 2017 (pre-pandemic) and 2020 (peri-pandemic). The effects of stress levels from COVID-19 and previous experience with sharing lodging services on risk perception changes were also examined.

Consumers showed higher social, physical, performance and convenience risk perceptions during the pandemic. Not surprisingly, those respondents who were more conscious of the pandemic in terms of concern and anxiety had higher changes in their risk perceptions. In addition, changes in risk perception differed by consumers' usage experience.

The results of this study add to the body of knowledge about consumers' risk perceptions of the sharing economy, particularly in connection with a huge disruption such as the COVID-19 pandemic.