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Research done to date has produced a wide range of perspectives that center on the junction between the specific function and responsibility of the entrepreneur when applying ethical dimensions to the field of entrepreneurship. By combining a bibliometric analysis with the literature review, the purpose of this paper is to provide an overview of entrepreneurship ethics and its contribution to sustainable development goals, along with future research directions on the topic of entrepreneurship and ethics.

The research looked for literature based on entrepreneurship ethics from the Dimension database. The authors accumulated 2,279 articles for the period of 2002–2022 for analysis. The authors used bibliometric analysis for analyzing the topic with the use of VosViewer and Excel.

By combining a bibliometric analysis with a literature review, this study aimed to provide an overview of the ethics and entrepreneurship and contribution to sustainable development goals. The most influential author and journal are Vanessa Ratten and the Journal of Business Ethics, respectively. The top sustainable development goals (SDGs) being contributed by entrepreneurship ethics are SDG4, SDG8, SDG16, SDG11 and SDG3. By contrasting these two interpretations, the authors have demonstrated that the entrepreneurship environment involves various ethical issues connected to personal, organizational and societal sectors.

The current study may serve as a general guideline for future investigation into this topic.

Regarding the practical ramifications, the findings can help entrepreneurs who are preparing to launch a business or are already doing so. The findings provide a comprehensive framework of success variables that must be considered to improve the venture’s performance.

This study’s originality is from presenting a structured and in-depth literature review that describes the current state of entrepreneurship ethics and its contribution to sustainable development goals. A complete analysis of the data gathered on entrepreneurship ethics is offered to establish that it is sustainable.

This study aims to examine the value orientations of New Zealand agribusiness investors and how these orientations influence their reactions to the environmental and social implications of agribusinesses.

In the context of the New Zealand agricultural sector, the views of investors as published in print and broadcast media between 2018 and 2022 are gathered. The study uses qualitative content analysis to analyse the data. The study is based on the value-belief-norm theory.

The study reveals that New Zealand agribusiness investors express concern about the environmental (biospheric) and social (altruistic) impacts of the agribusiness sector, prompting calls for greater transparency, climate adaptation and ethical investment options. Additionally, they actively support local businesses to benefit their communities and preserve cultural heritage. Despite these biospheric and altruistic tendencies, investors also prioritise financial and non-financial interests (egoistic). This highlights a nuanced perspective guiding their investment choices – a balance between self-interest and contributing to the greater good. This signals a shift towards socially and environmentally responsible investment practices driven by multifaceted values.

The findings of this study highlight the role of non-pecuniary motives, like values, in determining the relevance of environmental and social information.

The study’s findings offer insight to agribusinesses on how investors’ value orientations shape their investment decisions. This understanding can guide businesses in framing a reporting strategy that enhances the likelihood of investors perceiving reporting as relevant and persuasive, thereby attracting more investments. In turn, this tailored reporting approach assists investors in making well-informed decisions in assessing the environmental and societal risks of agribusinesses.

The study offers a framework explaining how agribusinesses can increase the likelihood of investors finding firms reporting relevant and persuasive, leading to increased investments in environmentally and socially sustainable practices.

This study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs).

A structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses.

The findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact.

The study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents.

Managers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions.

The study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers.

This study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

With revolutions in the telecommunication sector having led to wide unprecedented consequences in all facets of human life, this paper aims to examine the relationship between cell phone tower base stations (CPTBSs) and residential property prices within the City of Johannesburg (CoJ), South Africa.

The authors align their work with global literature and assess how the impact of CPTBSs influences residential property values in South Africa. The authors use a semi-log hedonic pricing model to test the hypothesis that proximity of CPTBSs to residential properties does not account for any variation in residential property prices.

The results show a significant impact that proximity of CPTBS has on residential property sale prices. However, the impact of CTPBSs’ proximity on residential property prices depends on their distance from the residential properties. The closer a residential property is to the CTPBS, the greater the impact that the CTPBS will have on the selling price of the residential property.

With international studies offering mixed findings on the impact of CPTBSs on residential property values, there is limited research on their impact in South Africa. The findings of this study offer crucial insights for the real estate practitioners, property owners, telecommunications companies and the public, providing a nuanced understanding of the relationship between CPTBSs and property values. This research helps property owners understand the effects of CPTBSs on their properties, and it assists property valuers in gauging the impact of CPTBSs on property values.

The prolonged training time of the neural network (NN) has sparked considerable debate regarding their application in the field of optimization. The purpose of this paper is to explore the beneficial assistance of NN-based alternative models in inductance design, with a particular focus on multi-objective optimization and uncertainty analysis processes.

Under Gaussian-distributed manufacturing errors, this study predicts error intervals for Pareto points and select robust solutions with minimal error margins. Furthermore, this study establishes correlations between manufacturing errors and inductance value discrepancies, offering a practical means of determining permissible manufacturing errors tailored to varying accuracy requirements.

The NN-assisted methods are demonstrated to offer a substantial time advantage in multi-objective optimization compared to conventional approaches, particularly in scenarios where the trained NN is repeatedly used. Also, NN models allow for extensive data-driven uncertainty quantification, which is challenging for traditional methods.

Three objectives including saturation current are considered in the multi-optimization, and the time advantages of the NN are thoroughly discussed by comparing scenarios involving single optimization, multiple optimizations, bi-objective optimization and tri-objective optimization. This study proposes direct error interval prediction on the Pareto front, using extensive data to predict the response of the Pareto front to random errors following a Gaussian distribution. This approach circumvents the compromises inherent in constrained robust optimization for inductance design and allows for a direct assessment of robustness that can be applied to account for manufacturing errors with complex distributions.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

Scholarship on America’s K-12 economics curriculum reveals an inattention to many harmful economic realities, specifically wealth inequality. Critics of the present curriculum posit that its emphasis on out-dated concepts and models ignores crucial elements of reality that impact economic interaction and identities. In response to the dominant economic paradigm and methods, this practitioner-focused paper discusses an economically pluralist, pedagogically critical approach to interrogating destructive economic realities. It details how three social studies classroom simulations based on the board game Monopoly may be integrated with certain informational texts to explore economic factors that contribute to America’s unique form of wealth inequality.

This paper describes wealth inequality in America and rationalizes the need to make this social problem a focus of study in the secondary social studies classroom. First, I survey the present curricular apparatus of K-12 economics education and then argue for a pluralist approach that expands the curriculum’s dominant neoclassical paradigm. Connecting economic pluralism to critical citizen education, I draw upon emerging critical economic citizen education scholarship to explain attendant pedagogical and instructional approaches. The described lesson builds upon a tradition of Monopoly simulations, is rooted in critical citizen education pedagogy and aligns with Soroko’s (2023) critical economic literacy framework.

This paper progresses the curricular movement of economic pluralism through its critique of America’s current K-12 economics curriculum that does not focus on immediate, lived social problems. It further defines critical economics, citizenship and pedagogy, then details an instructional practice that employs critical disciplinary tools to investigate contributing factors of American wealth inequality.

This paper contributes to the growing field of pluralist economic perspectives and pedagogies. Specifically, it enriches understanding of critical economics citizenship education by further defining attendant pedagogy and explaining Monopoly as an instructional tool for critical economics citizen education. Previous works have discussed Monopoly’s utility for teaching various concepts within the social studies disciplines. This simulation lesson is unique in its instructional approach that merges simulation experiences with certain informational texts to cultivate critical economic knowledge of American wealth inequality and critical economic skills for critiquing and transforming oppressive economic realities.

Due to e-commerce growth, technological advancements and environmental concerns, developing a more nuanced service portfolio has become a critical issue for last-mile logistics service providers. Concurrently, consumers are adopting new modes of consumption. This paper aims to investigate the potential for last-mile logistics service providers to act as intermediaries in access-based consumption and to revitalise their service offerings through product-service systems – a pioneering strategy not executed in the market yet.

This strategic customer foresight study uses a quantitative survey of 1,000 respondents and an online focus group comprising 10 early adopter consumers to investigate emerging last-mile service models. Potential service concepts were identified through the survey, and two distinct concepts were subsequently selected for evaluation and co-development within the focus group. The research was conducted in partnership with an SME logistics company in Finland.

The consumers expressed selective interest in access-based consumption related to the proposed offering of essential household goods. Young adults and consumers in early middle age living in the city centre emerged as the most potential user groups. Economic reasons and short-term needs were the primary motivations for adopting access-based consumption.

The study showed that engaging consumers in a customer foresight process is viable for SMEs innovating their offerings and demonstrates how the process works in practice.

Documented cases of customer integration into foresight processes are rare in earlier research, and this paper extends the knowledge base through a multidisciplinary examination of future consumer behaviour in the last-mile logistics domain. The paper also expands the limited literature on the role of logistics in access-based consumption.

This paper seeks to demonstrate the pedagogical potential of incorporating virtual reality (VR) and primary sources in social studies education. It seeks to highlight how VR can enhance student engagement, foster critical thinking and provide immersive contextualization for historical events. Despite acknowledging challenges, this paper advocates for the purposeful adoption of VR technology in the classroom to enrich the teaching and learning of history.

This paper explores the integration of virtual reality and primary sources in social studies education by providing a detailed lesson plan that could be used as a model for this type of teaching, as well as other resources and opportunities to do so. It highlights the potential of VR to enhance engagement, historical thinking and historical empathy.

Integrating virtual reality and primary sources can support student engagement, critical thinking and historical empathy. There are also challenges that can be mitigated through careful planning.

This paper provides teachers with a pedagogical model and resources for integrating VR and primary sources, along with challenges and methods for mitigating those, in their secondary social studies classroom.

This paper offers a unique model for combining virtual reality and primary sources for secondary social studies educators. It provides an example lesson plan exemplifying its application and emphasizing VR’s potential to support teaching and learning.

The purpose of this short communication is to shed light on the accuracy of quantification methods of household food waste (HFW).

Thirty-seven recently published studies in HFW were surveyed for this commentary. Exemplary methods and findings of these studies were compared.

It is challenging to draw conclusions on the amount of the HFW per person/town/country due to the inconsistent and heterogeneous methodologies used. We recommend using direct measurements or triangulation of methods to help ensure valid findings. Governments should incentivize consumers to deliver their food waste to designated locations where weights could accurately be assessed. Monetary or tax incentives could help stimulate an accurate accounting of waste and encourage reductions. Food waste measurements should be consistently reported as kg/person/week.

Food and water security must be provided for all. It is estimated that one-third of edible food for humans is currently lost or wasted globally. According to the World Food Program (WFP), this is about 1.3 billion tons of food per year and at the same time this wasted food could be sufficient to feed two billion people.

The aim of this paper is to fill a gap in the literature about the magnitude and significance of HFW and its impact on the environment and social welfare. Currently, there are no generally accepted uniform methods of food waste quantification at the household level. This original communication brings the importance and challenges of the quantification of HFW to light.