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This study aims to present a step-by-step implementation of the culturo–techno-contextual approach (CTCA) in a university classroom to teach industry and competitive analysis in the Ghanaian undergraduate entrepreneurship development curriculum. It further investigates the efficacy of the CTCA in breaking difficulties related to the study of industry and competitive analysis as a difficult concept in the Ghanaian entrepreneurship development curriculum. In doing this, the CTCA is compared with the lecture method.

The study adopts a quantitative approach. A quasi-experimental design is employed to gather data from 215 level 400 (4th-year undergraduate students) entrepreneurship development students at a Ghanaian public university. The experimental group was taught with CTCA, while the control group used the lecture method. The data was collected using the industry and competitive analysis achievement test (ICAAT). As random assignment to experimental and control groups were not possible, the data were subjected to an analysis of covariance approach with pre-test scores added as a covariate.

The results show that the experimental group significantly outperformed the control group. The results further indicate the efficacy of CTCA in improving undergraduate students’ performance in complex concepts of entrepreneurship.

Researchers usually test alternative teaching methods to break down barriers to study difficulties. The study’s uniqueness stems from the CTCA’s ground-breaking application to the study of entrepreneurship development in a Ghanaian public university.

The problem of environmental pollution is becoming increasingly severe, and international consensus confirms the need for eco-friendly consumption. Worldwide, the eco-friendly food market is booming, so understanding consumers’ motivations to purchase these foods is crucial. This paper aimed to construct a model explaining consumers’ intentions to purchase eco-friendly food by combining stimuli-organism-response (SOR) and signalling theories and exploring the mechanisms by which macro- and micro-signals impact perceptions of value and consumers’ subsequent willingness to purchase eco-friendly food.

An online questionnaire was distributed through the Qualtrics platform, and the completed questionnaires were collected in March and April 2023. The study used partial least squares structural equation modelling (PLS-SEM) to analyse the 331 valid responses received.

The results indicated that trustworthy eco-labels for high-quality and health-promoting products, as conveyed in macro signals, significantly enhanced consumers’ perceptions of functional value. The peer effect and a moderate level of food anthropomorphism conveyed in micro-signals substantially improved their perceptions of social value, whilst the perceived value of products significantly and positively influenced their purchase intentions.

This study explains consumers’ motivations to purchase eco-friendly products. This provides an explanation for the effect of macro- and micro-signals on value perceptions. By integrating the different dimensions of these signals to create a unified research perspective, the paper provides an integrated model, thereby filling a research gap concerning the influence of two-dimensional signals on purchase intention. By supporting eco-friendly food use, the paper contributes to environmental protection and sustainable development.

This paper aims to provide a comprehensive bibliometric study of housing prices according to the articles collected by the Web of Science (WOS).

This paper studies 4,125 research papers on housing prices in the core collection database of WOS. Using VOSviewer, this paper makes a bibliometric and visual analysis of the housing prices research from 1960 to 2020 and probes into the housing prices research from five aspects: time, international cooperation, institutions author cooperation and research focuses.

Keywords such as influencing factors of housing prices, analysis of supply and demand, policy and housing prices and regional cities appear frequently, which indicates the main direction of housing price research literature. Recent common keywords include regression analysis and house price forecast. Countries, like the USA started early in the study of housing prices, and the means and methods in the field of housing price research are mature, leading the forefront of housing price research. Compared with the USA and other Western developed countries, the housing price research in developing countries needs to use innovative research methods and put more effort on sustainability. Research shows that housing price is closely related to economy, and keyword cluster analysis shows that gross domestic product, interest rate, currency and other keywords related to economy are of high-frequency.

This paper only uses articles from one database (WOS), which does not represent all research papers published worldwide. Some studies have been published for a long time, and the reference value to the research focuses and future research might be limited. There are many kinds of journals included in the study with different publishing frequencies, time ranges and numbers of papers. These may have some influence on the research results.

The main theoretical contribution of this paper is to supplement the current academic research on housing prices. This paper reveals the key points of housing prices research and possible research problems that need attention. We can know from the future research direction and practice which can offer insights for future innovative direction.