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The purpose of this paper is to supply an in-depth description of the educators’ values, beliefs and confidence changing from a traditional learning environment to a learning environment integrating technology.

The descriptive case study design was employed using descriptive statistical analysis and inductive analysis on the data collected.

Themes on a high level of confidence, the importance of professional development and training, self-motivation, and excitement about the way technology can enhance the learning, along with concerns over the lack of infrastructure and support for integrating technology, and about the ability of students to use the technology tools for higher ordered thinking surfaced.

Additional research may include a more diverse population, including educators at the kindergarten to high school level. Another recommendation would be to repeat the study with a population not as vested in technology.

A pre-assessment of the existing values, beliefs and confidence of educators involved in the change process will provide invaluable information for stakeholders on techniques and strategies vital to a successful transition.

To effectively meet the learning styles of Generation Z and those students following, educators need be able to adapt to quickly changing technology, be comfortable with students who multitask and be open to technology-rich teaching and learning environments.

This study filled a gap in the literature where little information on the humanistic challenges educators encounter when integrating technology into their learning environment providing insights into the values, beliefs and level of confidence of educators experiencing change.

This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method.

In this context, data sets containing daily opening and closing prices between 2001 and 2019 have been created for 11 stock market indexes in the world. The association rule algorithm, one of the data mining techniques, is used in the analysis of the data.

It is observed that the US stock market indices take part in the highest confidence levels between association rules. The XU100 stock index co-movement with both the European stock market indices and the US stock indices. In addition, the Hang Seng Index (HSI) (Hong Kong) takes part in the association rules of all stock market indices.

The important issue for data sets is that the opening/closing values of the same day or the previous day are taken into account according to the open or closed status of other stock market indices by taking the opening time of the stock exchange index to be created. Therefore, data sets are arranged for each stock market index, separately. As a result of this data set arranging process, it is possible to find out co-movements of the stock market indexes. It is proof that the world stock indices have co-movement, and this continues as a cycle.

The main purpose of this research is to investigate factors influencing rural women entrepreneurship development and sustainable rural livelihoods in Manicaland province of Zimbabwe.

A quantitative research was conducted in Manicaland province in Zimbabwe. Data were collected through structured questionnaires from 400 women entrepreneurs in various sectors. The participants were in vegetable vending, operating clothing flea markets and cross border trading. A self-administered structured questionnaire was used to collect data from respondents. Structural equation modeling in SmartPLS version 3 was used to test the research hypotheses.

The study established that women entrepreneurship is driven by financial factors, positive environmental factors, positive psychological factors as well as positive sociological factors for a sustainable rural livelihood.

It is clear that if the discovered challenges are not addressed, sustainability of women entrepreneurship will remain a dream.

The study came up with strategies for improving women entrepreneurship activities. Future research can be done in other areas of provinces to avoid generalization challenges.

Many challenges hinder the sustainability of women entrepreneurship. Major impediments to women entrepreneurship comprises inadequate support from government schemes, patriarchal societal structure of the community, lack of relevant entrepreneurial knowledge to manage businesses, lack of collateral security to access funding, time limitation or role conflict to balance family pressures and business.

The study recommends proper entrepreneurship education and training, supportive government schemes and access to network affiliation/connection to sustain women entrepreneurship.

This study aims to examine the influence of service quality, satisfaction, trust, value and commitment on hotel customers’ attitudinal and behavioural loyalty.

The authors analyzed the relationship between learning orientation (LO) and performance in micro, small and medium-sized enterprises (MSMEs) by investigating the moderating role of environmental dynamism to answer the need for systematic research of models between LO and firm performance (FP).

The authors investigated the (in)direct relationship between LO and FP. The authors collected data from 182 MSMEs operating in technology parks (TPs) in Poland. The authors used two methods in the quantitative empirical research. The authors used linear regression models to test the hypotheses, which allowed for a global assessment of relationships among all analyzed variables. Dynamic capabilities (DCs) framework guided the study.

The study results show that FP benefits from LO-related behaviors. LO is an important stimulant of FP. Meanwhile, the authors did not classify market dynamism (MD) as a moderator of the LO-FP relationship.

By design, the authors surveyed only MSMEs open to participate in the survey, which potentially limits generalizability. Furthermore, future researchers may consider other types of strategic orientations (SOs) to further explain the impact of multiple SOs on FP in specific industries.

This article presents arguments that allow for recognizing LO as a strategic organizational factor shaping FP.

The purpose of this article is to investigate the factors that explain the reasons why customers may be willing to use chatbots in Zimbabwe as an e-banking customer service gateway, an area that remains under researched.

The research study applied a cross-sectional survey of 430 customers from five selected commercial banks conducted in Harare, the capital city of Zimbabwe. Hypotheses were tested using structural equation modelling.

The research study showed that a counterintuitive intention to use chatbots is directly affected by chatbots' expected performance, the habit of using them and other factors.

To better appreciate the current research concept, there is a need to replicate the same study in other contexts to enhance generalisability.

Chatbots are a trending new technology and are starting to be increasingly adopted by banks and they have to consider that customers need to get used to them.

This study contributes to bridging the knowledge gap as it investigates the factors that explain why bank customers may be willing to use chatbots in five selected commercial Zimbabwean banks. This is a pioneering study in the context of a developing economy such as Zimbabwe.

The study investigates the relationship between hospital environmental factors and the well-being of geriatric in-patients. It aims to identify the impact of architectural design on comfort, safety, privacy and stress levels experienced by elderly patients during their hospital stays.

Employing a mixed-methods approach, the research assesses the experiences of 100 geriatric in-patients across various hospital types through surveys, observational checklists and state anxiety measurements. The methodology involves examining architectural features, patient perceptions and correlations among environmental variables and patient experiences. Statistical analyses, including correlations and chi-square tests, were employed to discern associations between environmental variables and patient experiences.

The research identified key architectural features significantly impacting geriatric patients' experiences. Factors such as sturdy beds, furniture quantity, lighting conditions, proximity to facilities and ward occupancy levels were found to influence spatial, sensory and social comfort. Notably, proximity to facilities and control over the immediate environment were crucial for self-control and safety perceptions. Privacy, highly valued by patients, correlated with the presence of curtains and ward occupancy. Moreover, patient stress levels exhibited correlations with autonomy, privacy and ward occupancy.

This research offers significant insights into the criticality of specific architectural elements in enhancing comfort and reducing stress for geriatric in-patients. These findings hold substantial value for healthcare facility design, emphasizing the need to prioritize certain design aspects to promote the well-being of elderly patients during hospitalization.

The purpose of this paper is to look into the mechanism in which customers involve themselves in omni-channel retail setting and use its advantages.

Via an empirical analysis through surveying customers, this paper assesses and confirms the drivers of omni-channel shopping intention within the context of fashion retailing sector in Danang.

The findings highlight the significance of customer perception of research shopping (including showrooming and webrooming) behaviours, compatibility and risk to their intention towards omni-channel shopping, implying profound understanding of designing effective omni-channel retailing strategy.

From a theoretical perspective, comprehending customer perception of the omni-channel concept has emerged as an important theme in recent literature as well as in practitioners' reports. Hence, the meaningful contribution of this study is the involvement in the attractive steam of study. From a managerial perspective, this study could offer guidance to retailers or managers about developing a successful omni-channel strategy from a customer point of view.

Confidence intervals play a crucial role in economics and finance, providing a credible range of values for an unknown parameter along with a corresponding level of certainty. Their applications encompass economic forecasting, market research, financial forecasting, econometric analysis, policy analysis, financial reporting, investment decision-making, credit risk assessment and consumer confidence surveys. Signal-to-noise ratio (SNR) finds applications in economics and finance across various domains such as economic forecasting, financial modeling, market analysis and risk assessment. A high SNR indicates a robust and dependable signal, simplifying the process of making well-informed decisions. On the other hand, a low SNR indicates a weak signal that could be obscured by noise, so decision-making procedures need to take this into serious consideration. This research focuses on the development of confidence intervals for functions derived from the SNR and explores their application in the fields of economics and finance.

The construction of the confidence intervals involved the application of various methodologies. For the SNR, confidence intervals were formed using the generalized confidence interval (GCI), large sample and Bayesian approaches. The difference between SNRs was estimated through the GCI, large sample, method of variance estimates recovery (MOVER), parametric bootstrap and Bayesian approaches. Additionally, confidence intervals for the common SNR were constructed using the GCI, adjusted MOVER, computational and Bayesian approaches. The performance of these confidence intervals was assessed using coverage probability and average length, evaluated through Monte Carlo simulation.

The GCI approach demonstrated superior performance over other approaches in terms of both coverage probability and average length for the SNR and the difference between SNRs. Hence, employing the GCI approach is advised for constructing confidence intervals for these parameters. As for the common SNR, the Bayesian approach exhibited the shortest average length. Consequently, the Bayesian approach is recommended for constructing confidence intervals for the common SNR.

This research presents confidence intervals for functions of the SNR to assess SNR estimation in the fields of economics and finance.

This research's main objective is to investigate the relationship between consumption expenditure and consumer confidence in the USA and to study their effects on US economic revivalism during and after the coronavirus disease 2019 (COVID-19) shock.

The authors use Michigan's monthly Consumer Sentiment Index and its five components from January 1978 to April 2020. The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios, by providing a projection until December 2021. It also estimates the time needed for recovery and offers guidance to policymakers on ways to contain the negative impacts of COVID-19 on the economy by restoring consumer confidence.

All scenarios show a gradual recovery of consumer confidence and consumption expenditure. This study recommends expansionary policies to encourage consumption expenditure to generate additional demand and boost economic growth and job creation.

Though this study is limited to the US consumer confidence index, it offers significant implications for marketers, customers and policymakers of other developed economies. The authors recommend expansionary economic policies to boost consumer confidence, raise economic growth and result in job creation.

The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios; by providing a projection until December 2021. It also estimates the time needed for recovery and guidance for policymakers on ways to contain the COVID-19 shock negative impacts on the economy by restoring consumer confidence.