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Methods to assess the authenticity and traceability of wines have been extensively studied as enhancers of food quality, allowing producers to obtain market recognition and premium prices. Among analytical techniques, the volatilome profile attained by gas chromatography coupled with mass spectrometry is acquiring more and more attention by the scientific community, together with the use of chemometrics

The volatilome profile of three varieties of blanc wines from the Collio area (namely Ribolla Gialla, Malvasia and Friulano) between Italy and Slovenia, was determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhancing the carbonyl compounds identification with O-(2, 3, 4, 5, 6-pentafluorobenzyl)-hydroxylamine with the aim of identifying the autochthonous Friulano variety.

A two-step chemometric approach based on an unsupervised technique (PCA) followed by a supervised one (PLS-DA) allowed to identify possible markers for discriminating the Friulano Collio variety from the others, in particular two chemical classes were identified by PCA (ketones and long chain esters). PLS-DA showed 87% accuracy in classification. A correct classification (i.e. non-Friulano Collio) of a group of wines obtained from the same grape variety but produced in an extra-Collio area was obtained as well. The results confirmed the benefits of using a derivatization step prior to volatile organic compounds analysis.

Among methods to assess the authenticity and traceability of wines, volatilome profile of wines determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhanced by the carbonyl compound identifications with O-(2, 3, 4, 5, 6-pentafluorobenzyl)-hydroxylamine, may have a key role in conjunction with chemometrics and, in particular with principal component analysis and partial least square discriminant analysis.

Among methods to assess the authenticity and traceability of Friulano wine, volatilome profile of wines determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhanced by the carbonyl compound identifications with O-(2, 3, 4, 5, 6-Pentafluorobenzyl)Hydroxylamine hydrochloride, may have a key role in conjunction with chemometrics.

Few works investigated both wine traceability with a volatilome enhancer and chemometrics of the Friulano wine variety obtaining such an improvement in this wine variety discrimination.

This study aims to determine how Internet of Things (IoT) risks and benefits affect both the intention to use and actual use of a smartwatch.

The stimulus–organism–behavior–consequence (SOBC) hypothesis is used to explain the mechanisms underpinning the discontinuity between intention and technology usage. A total of 394 questionnaires distributed to smartwatch users were analyzed, using convergent analysis, discriminant analysis and structural modeling.

The IoT’s technical features, such as continuous connectivity and real-time value, serve as effective stimuli for smartwatches, positively influencing individuals’ responses and behavioral consequences associated with smartwatch usage. While IoT risks such as data, performance and financial have no negative relationship with the usefulness of smartwatches, data and financial risks have a negative influence on their ease of use. Additionally, as ease of use and usefulness have a positive impact on intention to use, users’ behavior is positively influenced by their intentions to use a smartwatch.

The study applies technology acceptance theory and the SOBC paradigm to smartwatches to determine if users’ intentions to use them impact their behavior. Furthermore, the research analyzed the technical elements of smartwatches in terms of IoT advantages and risks.

El objetivo del presente estudio es determinar cómo los riesgos y beneficios del Internet de las Cosas afectan tanto a la intención de uso como al uso real de un smartwatch.

Se utiliza el modelo Estímulo-Organismo-Comportamiento-Consecuencia (SOBC) para explicar los mecanismos que sustentan la discontinuidad entre la intención y el uso de la tecnología. Se analizaron 394 cuestionarios distribuidos a usuarios de smartwatches, empleando análisis convergente, análisis discriminante y modelización estructural.

Las características técnicas del IoT, como la conectividad continua y el valor en tiempo real, sirven como estímulos efectivos para los smartwatches, influyendo positivamente en las respuestas de los individuos y en las consecuencias conductuales asociadas al uso del smartwatch. Mientras que los riesgos de la IO, como los datos, el rendimiento y los financieros, no tienen una relación negativa con la utilidad de los smartwatches, los riesgos de los datos y los financieros influyen negativamente en su facilidad de uso. Además, dado que la facilidad de uso y la utilidad tienen un impacto positivo en la intención de uso, el comportamiento de los usuarios está positivamente influenciado por sus intenciones de usar un smartwatch.

El estudio aplica la teoría de la aceptación de la tecnología y el paradigma SOBC a los smartwatches para determinar si las intenciones de uso de los usuarios influyen en su comportamiento. Además, la investigación analiza los elementos técnicos de los smartwatches en cuanto a las ventajas y los riesgos del IoT.

本研究的目的是确定物联网的风险和利益如何影响智能手表的使用意向和实际使用。

刺激-组织-行为-后果（SOBC）假说被用来解释意图和技术使用之间不连续的基础机制。对发放给智能手表用户的394份调查问卷进行了分析, 采用了收敛分析、判别分析和结构模型法。

物联网的技术特点, 如持续连接和实时价值, 作为智能手表的有效刺激, 对个人的反应和与智能手表使用相关的行为后果产生积极影响。虽然数据、性能和财务等物联网风险与智能手表的有用性没有消极关系, 但数据和财务风险对其易用性有消极影响。此外, 由于易用性和有用性对使用意图有积极影响, 用户的行为受到他们使用智能手表的意图的积极影响。

该研究将技术接受理论和SOBC范式应用于智能手表, 以确定用户的使用意图是否影响其行为。此外, 该研究还从物联网的优势和风险方面分析了智能手表的技术要素。

This study aims to analyze antecedents of students’ lack of proficiency (in preparing financial statements, cash flow statements, cost volume profit analysis and budgeting) and the need for an automated financial plan (AFP) for the course entrepreneurship creativity and innovation within Higher Educational Institutions (HEIs) in Oman.

The study used a set of four instrument items containing questionnaires to measure the variables in this study. A cross-sectional study was carried out at various universities and colleges in Oman during the year 2020, comprising 174 students from different majors. The results were analyzed using structural equation modelling-partial least squares.

The findings of the study suggest that the students in the universities and colleges should be educated and facilitated to enable them to gain more knowledge in finance/accounting through an AFP and, thus, warrants preparation of fair financial estimation for their innovative business project. A majority of students strongly support the need for implementing an AFP for their compulsory course, entrepreneurship creativity and innovation in HEIs in Oman.

This research is restricted to AFPs for the students in Oman who study the course entrepreneurship creativity and innovation. It is recommended that future study may extend to automated business plans for the students to improve their practical knowledge pertinent to the readiness of Omani students, as well as to give material transformation of internal environments in HEIs.

Unique AFP for university and college students for their compulsory course, entrepreneurship creativity and innovation provide important resources for policymakers responsible for HEIs, allowing them to improve the quality of preparing a financial plan for their innovative business ideas and new business start-ups.

There has been little discussion about the need for an AFP for the students who study the course entrepreneurship creativity and innovation. This study analyzes accounting standards as antecedents about students’ lack of proficiency towards an AFP for the course entrepreneurship creativity and innovation of universities and colleges in Oman which tries to fill this gap in the existing research. Hence, this study is considered as a novel approach that has not been broadly discussed in the earlier research.

This study aims to analyse the following: first, the financial performance of General Insurance Re (GIC Re) using performance ratios (PRs); second, the uniformity of different financial performance indicators of GIC Re; third, the internal growth capacity of GIC Re; and finally, the likelihood of GIC Re going into financial distress.

As a sample, GIC Re, the lion shareholder in Indian Reinsurance Industry has been considered in the present study. All the necessary data have been extracted from the secondary sources over a time period of 16 years. The financial performance of GIC Re is assessed using five standard ratios, and the uniformity of different financial performance indicators of GIC Re has been examined using Kendall’s Coefficient of Concordance (W). To assess the internal growth capacity of GIC Re internal growth rate has been used, and the likelihood of GIC Re going into financial distress is analysed using multivariate discriminant approach, namely, modified Altman’s Z-score model and logit analysis technique, namely, Ohlson’s O-score model.

The results exhibit that financial performance of GIC Re is somewhat satisfactory over a few considerable areas. However, no notable degree of uniformity has been observed amongst the varied financial performance indicators, namely, performance ratio, expense ratio, return on assets, risk retention ratio and combined ratio of GIC Re. The results also reveal GIC Re is lacking ability of growing internally. Moreover, there remains a significant possibility of GIC Re going into financial distress in the near future and so.

This study is one of the first empirical research studies in India that examines the financial performance of GIC Re from different perspectives.

The purpose of this paper is to determine the drivers of the formation of e-loyalty in a tourist destination, providing a model composed of variables that are under the control of the firm along with others that are not fully controllable by professionals.

The study was carried out with a sample of 497 subjects, university students and online consumers, and with the use of structural equations (partial least squares).

Results show that young people give a high valuation to all the variables used in the research. These results contribute to the literature on e-loyalty in tourism destinations and improve tourism loyalty in this population segment.

The main limitation of this research has been related to the number of variables and measurement indicators that, according to the literature review, influence e-loyalty. Finally, a balanced and statistically significant model has been developed that has practical utility and analyzes online purchase of tourism products from a process perspective that includes variables that are internal and external to the firm.

The study suggests that young people have a favourable attitude and predisposition towards e-commerce, which, in turn, favours firms’ efforts to promote consumption and loyalty within the framework of the model’s variables.

This research paper has important value by analysing the initiating variables to determine how e-loyalty can be managed in tourist destinations, in addition to analysing an important segment for future tourism development.

This study aims to identify the countries’ innovation factors that are determinant for them to achieve higher levels of development. In addition, the research identified which of these factors should be prioritized so the countries can move up in the rank of the most competitive.

The study used the indicators of innovation and the stage of development of 137 countries proposed by the Global Competitiveness Report published by the World Economic Forum and techniques of multivariate data analysis.

The results indicated that all the factors tested are determinant to lead the countries throughout their stages of development. The research highlights that the factors “Quality of scientific research institutions” and “Patent Cooperation Treaty (PCT) patent applications” should be equally prioritized for the countries’ development.

The results suggested that the factors Capacity for Innovation, Quality of Scientific Research Institutions, Company Spending on Research and Development (R&D), University–Industry Collaboration in R&D, Government Procurement of Advanced Technology Products, Availability of Scientists and Engineers and PCT Patent Applications are decisive for positioning countries in terms of their stage of development and should be part of their public policy and enterprises’ strategic planning.

The findings show that countries should prioritize the factors Quality of Scientific Research Institutions and PCT Patent Applications, as these factors, when acting together, predict the evolution to higher stages of development.

The purpose of the study was to ascertain the influence of innovation conviction, innovation mindset and innovation creed on the performance of women entrepreneurs in South African small and medium enterprises and their capacity for innovation. The study also examined how proactive personality and entrepreneurial education moderate the relationship between innovative capability and women entrepreneurs' performance.

The study used a quantitative research design and administered a questionnaire to collect data from participants. Since there was no sampling frame available, purposive sampling, a non-probability sampling technique, was used to select suitable respondents who were identified as entrepreneurial women. Data were collected from 304 women entrepreneurs in the Gauteng province of South Africa. The data were analyzed using smart partial least squares.

The findings demonstrated that innovation conviction, innovation mindset and innovation creed have a positive impact on innovation capability. It was also discovered that innovation capability, proactive personality and entrepreneurial education all positively and significantly impact women entrepreneurs' performance. Furthermore, the results showed that entrepreneurial education and proactive personality had a positive and significant moderating effect on the nexus between innovation capability and the performance of women entrepreneurs.

This study will add to the body of knowledge on women's small business management and entrepreneurship in Africa, two topics that are typically ignored by academics in developing nations.

This study aimed to assess the potential of the Clinical Dementia Rating (CDR) Scale in the prognosis of dementia in elderly subjects.

Dementia staging severity is clinically an essential task, so the authors used machine learning (ML) on the magnetic resonance imaging (MRI) features to locate and study the impact of various MR readings onto the classification of demented and nondemented patients. The authors used cross-sectional MRI data in this study. The designed ML approach established the role of CDR in the prognosis of inflicted and normal patients. Moreover, the pattern analysis indicated CDR as a strong cohort amongst the various attributes, with CDR to have a significant value of p < 0.01. The authors employed 20 ML classifiers.

The mean prediction accuracy varied with the various ML classifier used, with the bagging classifier (random forest as a base estimator) achieving the highest (93.67%). A series of ML analyses demonstrated that the model including the CDR score had better prediction accuracy and other related performance metrics.

The results suggest that the CDR score, a simple clinical measure, can be used in real community settings. It can be used to predict dementia progression with ML modeling.

This paper is to explore how cross-functional integration (CFI) of production-marketing can impact the firm's build-to-order (BTO) competitiveness, marketing performance (MP) and financial performance (FP).

Empirical study with the structural equation modeling approach is applied. Six hypotheses are constructed and tested based on survey data collected from Chinese manufacturing firms.

The survey data supports that production-marketing integration (PMI) improves BTO competitiveness (BTOC) and MP and that BTOC also positively affects marketing outcome which, in turn, impacts a firm's FP. The results reveal that CFI of production-marketing is an effective approach for achieving the BTO manufacturing strategy and can improve organizational performance.

The paper uncovers the role of CFI of production-marketing in BTO manufacturing strategy and its impacts on a firm's MP and FP and provides important managerial implications for practitioners to improve organizational time-based competitiveness and performance in today's time-based competition era.

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best form of variable for this problem. Because of MapReduce’s unsuitability for iteration problems involved in developing CB-FPMs, various BDA initiatives for iteration problems were identified. A BDA framework for developing CB-FPM was proposed. It was validated by using 150,000 datacells of 30,000 construction firms, artificial neural network, Amazon Elastic Compute Cloud, Apache Spark and the R software. The BDA CB-FPM was developed in eight seconds while the same process without BDA was aborted after nine hours without success. This shows the issue of not wanting to use large dataset to develop CB-FPM due to tedious duration is resolvable by applying BDA technique. The BDA CB-FPM largely outperformed an ordinary CB-FPM developed with a dataset of 200 construction firms, proving that use of larger sample size with the aid of BDA, leads to better performing CB-FPMs. The high financial and social cost associated with misclassifications (i.e. model error) thus makes adoption of BDA CB-FPMs very important for, among others, financiers, clients and policy makers.