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The purpose of this paper is to assess the adoption of climate-smart agriculture (CSA) and its implication on improving the farming household food security status, their resilience and livelihood risk management of farmers.

This systematic review has followed procedures to accomplish the review, including literature searches, screening studies, data extraction, synthesis and presentation of the data.

Based on the result of the review, the determinants of CSA adoption can be categorized into five categories, including demographic factors (age, sex, family size, dependency ratio, education), economic factors (land size, household income, livestock ownership), institutional factors (extension services, training access, credit services, farm input, market distance), environmental factors (agroecology, change in precipitation, slope of land) and social factors (cooperatives membership, farmers perception). The result also shows that applying CSA practices has an indispensable role on increasing productivity, food security, income, building resilient livelihoods, minimizing production risk and alleviating poverty. This concluded CSA practice has a multidimensional role in the livelihood of agrarian population like Ethiopia, yet its adoption was constrained by several factors.

This review mainly emphasizes on the most commonly practiced CSA strategies that are examined by different scholars.

This paper aims to utilize an extended involvement-commitment and trust commitment model to examine post-consumption decisions related to food delivery app use.

A self-administered online survey was used to collect data from food delivery app users in the USA.

Findings validate a favorable role of perceived app security and menu description on trust in app recommendations. Trust was found to be positively related to involvement, commitment and willingness to provide feedback. The positive moderating role of perceived convenience and rewards and incentives was also confirmed in relation to consumers’ trust in app recommendations, and involvement and commitment

A key contribution of this study includes the development of a comprehensive model to understand postconsumption decisions related to the usage of food delivery apps. To the best of the authors’ knowledge, this study is also the first to unveil the antecedent and moderating factors related to food delivery app users’ willingness to provide feedback, share personal data and to pay more.

The agricultural sector has experienced a transformative impact through the adoption of digital technologies, particularly mobile applications designed for farmers. This study investigates the factors influencing smallholder farmers' willingness to adopt digital application tools in Ogun State, Nigeria, focusing on the IITA herbicide calculator and Akilimo mobile applications.

Data were gathered from 572 smallholder farmers participating in the Zero Hunger project. This research contributes to the limited empirical evidence in Nigeria concerning farmers' willingness to adopt digital application tools. The study analyzes the effects of education, training, access to internet services, smartphone ownership, willingness to use paid applications, awareness of application tools and the cost of digital tools on farmers' willingness to adopt. Gender differentials in willingness to adopt were also explored.

The results indicate positive and statistically significant effects of education, training, internet access, smartphone ownership, willingness to use paid applications, awareness of application tools and the cost of digital tools on farmers' willingness to adopt. However, female farmers exhibited a lower willingness to adopt digital application tools.

Policymakers are urged to create supportive policies promoting basic formal education and provide effective extension services to enhance farmers' training. Additionally, efforts should be made to reduce the cost of digital applications and improve internet accessibility in rural areas. Encouraging female farmers to adopt advanced agricultural technologies is essential. Stakeholders are advised to raise awareness of digital application tools to expedite the adoption of agricultural technologies in the country.

This study will be helpful for the government to determine the state’s readiness for digital agriculture, it will help technology developers and agricultural technology startups to understand the factors determining farmers willingness to adopt digital application tools.

This study offers insights into the readiness of Ogun State, Nigeria, for digital agriculture. It provides valuable information for technology developers and agricultural startups to understand the determinants of farmers' willingness to adopt digital application tools, contributing to the advancement of the agricultural technology landscape.

Cooperatives are used as one of the strategic tools to reach smallholder farmers and reduce household poverty through augmenting access to inputs, technologies, farm productivity and markets. Our study aims to investigate the impacts of the Meki Batu Cooperative Union on reducing household poverty.

This study employed a cross-sectional survey of households in the Dugda district of the East Shewa zone in the Oromia region. A two-stage sampling design was applied, where four rural Kebeles were first randomly picked, followed by stratified random samples of 217 producers comprising 100 members and 117 non-members of cooperatives. The standard probit model was estimated with a set of observable factors. Propensity score matching (PSM), doubly robust inverse probability weighting and treatment effect estimation were performed along with matching techniques.

The results reveal that education, livestock assets, access to irrigation and extension contact positively determine participation in cooperatives. As the income-based poverty attests, the poverty gap was reduced by 5.9–6.3% and the severity of poverty by 3.7–3.8% due to the cooperative membership.

The investigation suggests the need for continued and comprehensive social services to address development challenges through the facilitation of producers’ engagement in collective actions and agribusinesses.

Existing research evidence is inconclusive with the view of impacts of collective actions on housed welfare in Ethiopia. This study empirically tested the impacts in connection to the production and marketing of high-value crops.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2024-0231

Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

The aim of this study is to examine the availability, utilization and effectiveness of various information sources in enhancing the knowledge and practices of Lakadong turmeric farmers.

This study focuses on 125 Lakadong turmeric farmers in Myntkung and Biar villages, Meghalaya, India. A purposive sampling technique was used to select participants, ensuring the representation of various ages, experiences and agricultural practices. A mixed-methods approach was used, including structured interviews and focus group discussions, to gather information on the farmers.

The study found that most of the Lakadong turmeric farmers (35.2%) needed information on farming techniques and practices and 93.6% of farmers approached their friends, relatives or fellow farmers to access any information. For most farmers, 77 (62%) relied on word-of-mouth to get information. After using the information effectively and efficiently, most farmers (46.4%) agreed that there was an increase in Lakadong turmeric yields, improved crop quality and reduced pest infestation.

The study highlights informational gaps in the agricultural sector, empowering farmers to explore alternative sources. It suggests that understanding farmers’ unique needs can improve agricultural extension agencies’ programs and resources. Policymakers should invest in digital literacy programs and regional information resources. The study also suggests integrating information literacy training into agricultural operations, fostering collaboration among farmers, institutions and information providers. The geographical indication tag on Lakadong turmeric can also empowers local communities by fostering economic opportunities through the promotion and protection of this prized spice.

Existing research tends to focus more broadly on agricultural information dissemination or other crops, leaving a notable gap in the literature regarding the unique informational needs and access challenges faced by Lakadong turmeric farmers.

The purpose of this study is to examine the factors that may have an influence on the continuous intention to use mobile money as one of the Financial Technology (FinTech) products beyond the COVID-19 pandemic lockdown period.

This study has empirically tested the expanded post-acceptance model (Extend-PAM) and the expectation-confirmation model (ECM) to explain the mobile money adoption in Jordan. Data collected were analyzed through partial least squares–structural equation modeling (PLS-SEM).

The results mainly showed that the quality of administrative services and trust significantly impact confirmation and perceived usefulness. In addition, perceived security and knowledge of mobile money as one of the FinTech services significantly influence users’ confirmation and perceived usefulness. Also, usefulness and satisfaction influence continuous intention. Significant relationships were noted among confirmation, perceived usefulness, satisfaction and continuous intention to use mobile money.

This paper integrates two key theories: the expanded post-acceptance model (Extend-PAM) and the expectation-confirmation model (ECM) in the post-adoption behavior of mobile money. Therefore, this study attempts to fill a literature gap by examining the antecedent factors that influence the continuous intention to use mobile money services in the post-consumption stage.

How does business model design play a role in enabling manufacturing firms’ services? This study aims to investigate the impact of two distinct types of business model design, namely, efficiency-centered business model design (EBMD) and novelty-centered business model design (NBMD), and their effects in balanced and imbalanced configurations, on two types of services: product- and customer-oriented services.

Using matched survey data of 390 top managers and objective performance data of 195 Chinese manufacturing firms, this study uses hierarchical regression, polynomial regression and response surface analysis to test the hypotheses.

The results show that while EBMD positively affects product-oriented services, NBMD positively affects customer-oriented services. Both types of services exert a significant influence on firm performance. Furthermore, the degree of product- and customer-oriented services increases with an increasing effort level with a balance between EBMD and NBMD. Asymmetrical, imbalanced configuration effects reveal that the degree of product-oriented services is higher when the EBMD effort exceeds the NBMD effort, and the degree of customer-oriented services is higher when the NBMD effort exceeds the EBMD effort.

This study enriches the understanding of designing business models to facilitate service growth in manufacturing firms, ultimately benefiting firm performance. In addition, exploring balanced and imbalanced configurations of EBMD and NBMD offers new insights into business model dual design research.

This study aims to evaluate the information behavior of the Banarasi Sarees weaving community and propose an information-focused policy tailored to their needs.

This study was conducted in seven weaver-centered areas in Varanasi and was designed around semi-structured interviews to explore various information-related aspects among the weavers. It aims to focus on their knowledge of weaving, their information needs, seeking behavior, preferred communication channels, prioritization of information and methods for enhancing information-related situations.

It was found that a lack of information among weavers significantly impacts their livelihoods and businesses. They struggle to make product, pricing and marketing decisions without access to accurate, timely and relevant information. They cannot expand their businesses and invest in new equipment and materials. The weavers need a library with a specialized collection and a qualified librarian to guide them in using the information sources. They also need a dedicated information system and community information centers to provide better information services.

This study is a work whose expected results and findings would help policymakers adopt measures to encourage providing information services through public libraries and community information centers. The results of this study may be further used to frame information policy for weavers and other occupational communities.

This study aims to address the following research questions: (1) What are the theoretical frameworks and areas of study that influence the development of service ecosystems? and (2) To what extent does a service ecosystem align with the theoretical concepts presented in other research contexts within the study areas, thereby transforming the fundamental structure of the core concept?

We conducted a bibliometric systematic literature review, analyzing 280 papers from a sample of 52 journals listed in the Association of Business Schools (ABS). The review covered the period between 2004 and 2022, and we utilized co-citation analysis, multi-dimensional scaling analysis and hierarchical cluster analysis (HCA) on a total of 2,614 citations.

This study employs co-citation analysis to identify the conceptual structure of the service ecosystem based on highly cited papers. Additionally, we utilize multidimensional scaling (MDS) to uncover key approaches driving service ecosystem research. Through HCA and network analysis, we examine the research scope and its development, emphasizing theory-driven approaches. By combining quantitative and qualitative analysis, we explore the interrelationships between scope, domain and evolution. This comprehensive analysis allows us to delve deeply into the study of service ecosystems. To broaden the research scope, we propose a conceptual framework for comparing the main components of a service ecosystem. The current paper clarifies the service ecosystem's intellectual structure, including service performance, humanistic approach, sustainable innovations and service reflexivity and reformation and proposes a prospective research framework for specialists and researchers by introducing a metaverse service ecosystem.

For the first time, the findings of this study shed light on processes that facilitate the flow of technologies, business models and markets through social structures, ultimately contributing to social change. In service-based systems, the development and application of a more humanistic approach within and surrounding social service ecosystems are crucial as they evolve. Therefore, adopting a dynamic and multifaceted approach offers valuable insights into the drivers of value creation.