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The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of computer science education.

This study adopted the quasi-experimental design to determine the efficacy of the CTCA in breaking difficulties related to the study of spreadsheets as a difficult concept in the Nigerian computer science education curriculum. Junior high school students studying computer science education participated in the study. The control group had 30 students, with 35 students in the experimental group. The experimental group was taught using CTCA, while the control group used the lecture method. The spread sheet achievement test, which had 40 items on spreadsheet, was used to collect data.

The results showed that the experimental group significantly outperformed the control group [F (1,60) = 41.89; p < 0.05]. The findings showed the potential of CTCA in improving students' performance in spreadsheets in the computer science education curriculum.

The originality of this study is hinged on its ground-breaking test of the CTCA to the study of the spreadsheet. The findings of this study indicate its efficacy in improving students' understanding of spreadsheet and computer science education.

This research aims to explore the significance of cooperative efforts in promoting financial participation to enhance the socio-economic empowerment of the rural Muslims.

The primary study with a structured questionnaire has been conducted taking a sample of 398 rural Muslim respondents from various rural regions of south India through proportionate stratified sampling techniques. Regression analysis, paired sample t-test and structural equation modelling (SEM) through statistical package for social sciences (SPSS) 26 & SPSS analysis of moment structures (AMOS) 23 software have been implemented to test the relationship.

The research outcome demonstrated a remarkable difference in the rural Muslim’s socio-economic conditions before and after availing the loans from cooperatives. Consequently, an extension of cooperative efforts widens the scope of financial participation which again has positively enhanced rural Muslim’s socio-economic empowerment.

This study will help various policymakers, academicians and communities to take necessary action for the upliftment of a particular community. The research further adds on to the existing research on the need and importance of cooperative efforts as an alternative finance for marginalised community in developing and emerging countries.

The result of this study is only confined to south India, posing a limitation for the study. Apart from the geographical restriction, the study solemnly covers the rural Muslim community extracting other sections of the society. Hence, for more generalisable pictures of the current results, further research is recommended from other stakeholders’ perspectives.

In this article, we reflect on how smart technology is transforming service research discourses about service innovation and value co-creation. We adopt the concept of technology smartness’ to refer to the ability of technology to sense, adapt and learn from interactions. Accordingly, we seek to address how smart technologies (i.e. cognitive and distributed technology) can be powerful resources, capable of innovating in relation to actors’ agency, the structure of the service ecosystem and value co-creation practices.

This conceptual article integrates evidence from the existing theories with illustrative examples to advance research on service innovation and value co-creation.

Through the performative utterances of new tech words, such as onlife and materiality, this article identifies the emergence of innovative forms of agency and structure. Onlife agency entails automated, relational and performative forms, which provide for new decision-making capabilities and expanded opportunities to co-create value. Phygital materiality pertains to new structural features, comprised of new resources and contexts that have distinctive intelligence, autonomy and performativity. The dialectic between onlife agency and phygital materiality (structure) lies in the agencement of smart tech–enabled value co-creation practices based on the notion of becoming that involves not only resources but also actors and contexts.

This paper proposes a novel conceptual framework that advances a tech-based ecology for service ecosystems, in which value co-creation is enacted by the smartness of technology, which emerges through systemic and performative intra-actions between actors (onlife agency), resources and contexts (phygital materiality and structure).

The study aims to identify the trends in the scholarly works on investors preference toward sustainable investments by synthesizing their knowledge structures.

A systematic search approach using PRISMA protocol on the Scopus database was used to generate a sample of 403 publications for the purpose of bibliometric analysis. The study performed a range of analyses, including three-field plot analysis, thematic mapping and cluster analysis using the VOSviewer and Biblioshiny software.

The key findings comprise the identification of four clusters within the subject, namely, corporate social responsibility and environmental, social and governance (ESG) investing, ethical investing, green finance and socially responsible investments. This study offers a clear picture of the publishing advancement and research diversification of four selected clusters' research themes, and cluster subthemes.

The research reveals the social and intellectual structure of the field, which provides the future researchers an insights into emerging themes and provides them opportunities for collaboration as well. The outcomes of the research hold significance for policymakers, governing bodies, aspiring scholars, advocates for the environment and investors. It offers an insightful framework for implementing sustainable practices, balancing profits, and environmental risks and creating value from environmentally conscious research and practice.

The future direction and extensiveness of research work have been explored using the themes generated. To the best of the authors’ knowledge, this study, which combines the VOSviewer and Biblioshiny tools, is likely the first attempt to provide a thorough bibliometric analysis in the research sphere of investors preferences toward sustainable investments.

There is limited knowledge of the sustainable halal food supply management in Brunei Darussalam (Brunei), although it is reputable in the halal economy and advocates the United Nations (UN) Sustainable Development Goals (SDGs). Therefore, this paper highlights issues faced in a small, rentier halal market and proposes sustainable supply chain management (SSCM) initiatives for halal-certified food companies in Brunei.

This paper draws data from published academic research and employs a normative and narrative assessment of SSCM and halal supply chain literature.

Four normative SSCM initiatives and propositions that could be implemented by Brunei halal-certified food businesses in achieving the SDGs are highlighted: responsible sourcing, environmental purchasing, sustainable packaging and green transportation.

This viewpoint paper provides a basis for achieving the “Brunei Vision 2035” through a sustainable supply chain lens that may increase well-being and develop a productive and sustainable economy. It also lays a foundation for realising the SDGs, specifically Goal 12 of Sustainable Consumption and Production.

The dedicated attention to smaller halal markets, such as Brunei, would enrich the literature, reveal unforeseen issues or address gaps in the domains of SSCM and halal food supply chains.

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.