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The purpose of this paper is to analyse the role of quality management on the development of organisational exploration.

Partial Least Square was used on a sample of 350 companies within the Spanish organic agro-food industry.

The study results provide empirical evidence of the positive and significant impact that quality management has on the development of organisational exploration.

Causal relationships cannot be applied to this study due to cross-sectional data being used rather than longitudinal data.

Quality management must be considered by managers an essential tool to the development of organisational exploration. As a systematic approach, that moves towards to the development of policies, attitudes and behaviours which foster and boots the development of organisational exploration.

Quality management is a widely used management approach, which organisations use to improve the quality of their products, services and their overall performance. Organisational exploration is seen as a fundamental tool to ensure sustainability, profitability and the future survival of organisations; however, there is disagreement throughout previous research. Some authors point out the importance of quality management in developing activities that promote organisational exploration, whereas other authors see quality management as an inhibitor. Given the great controversy in previous research, our study clarifies the role of quality management in the development of organisational exploration.

The aim of this study is to provide an empirical investigation of the agricultural cluster’s economic, social and environmental values. By doing so, the authors aim to offer policymakers and decision-makers a strategic approach that promotes competitiveness and economic development through shared value.

The authors used AMOS software and applied structural equation modeling to achieve the study’s objectives. The study used this approach with path analysis through the Analysis of Moment Structures software.

The empirical results indicate that creating shared value (CSV) can enhance the agricultural sector’s competitiveness through clustering. Rather than enhancing competitiveness directly, CSV plays a crucial role in improving the relationship between clustering and competitiveness. The authors also examined Porter’s diamond of competitiveness and evaluated factors for creating a shared value strategy, such as factor conditions, demand conditions, related and supporting industries, strategy, structure, rivalry and the role of government.

This study focuses solely on the agricultural cluster in Qalqilya governorate and cannot be applied to other regions without additional research.

Ensuring that stakeholders in the agricultural sector are kept informed about the activities of the cluster and the benefits of their participation is crucial. Empirical findings and conclusions have demonstrated that a shared value strategy can enhance the competitiveness of this sector. To achieve this, institutions involved in developing the agricultural cluster must increase their efficiency and capacity. Consulting experts in this field and drawing on experiences from other countries can aid in achieving this goal. Additionally, enhancing farmers’ productivity should be a priority, and the Ministry of Agriculture can provide training and workshops to improve their skills and expertise.

This study suggests that Palestinian policymakers should establish effective partnerships between the government and the agricultural sector’s firms in Qalqilya to reinforce the cluster’s competitiveness. This strategy can stimulate competitiveness and promote economic and social development in Palestine.

This research analyses the impact of customers and government regulations on the implementation of socio-environmental practices in certifying organic agricultural products. It explores the dyad’s relationship between the focal company and its suppliers in the application of socio-environmental practices.

This study uses a quantitative methodology through a survey approach, with a sample of 206 agro-extractivists from the acai berry supply chain. The data are evaluated using regression analysis.

The main results reveal that customer pressure positively influences the implementation of social and environmental practices, but suggest a non-significant relationship between government regulations and the impact on environmental practices implementation. Social and environmental practices are positively related to operational performance. A moderating effect of organic certification is found in the relationship between customer pressure and the application of environmental practices.

The main contributions are exploring the use of socio-environmental practices in an emerging economy and organic certification as a moderating variable, revealing an “institutional void” that may hamper the enforcement of government regulations.

This study aims to find how trade development and digitalization affect smart-green production. Four factors are investigated in these effects (certification, technology innovation, natural resource management, low pesticides).

The mix-method approach was employed from validating the measurement scale to test the proposed hypotheses. At first, the grounded theory is the most authoritative and standard research method in qualitative research. Secondly, quantitative analysis was employed to draw conclusions about the impact of digitalization and trade development on smart-green agricultural production.

The results found that digitalization and trade development impact the development of smart-green agricultural production through certification employment, technology innovation, and a decrease in pesticide usage. Moreover, digitalization and trade development also indirectly affect the development of intelligent green agricultural production. Meanwhile, digitalization has a higher impact than trade development.

This research is based on the premise that digitalization and trade development can drive smart green agricultural production. Still, some studies have found a deviation between trade development and environmental protection. Hence, future research can explore the incentive effect of trade development and digitalization on other industries. Second, the measurement of the dependent variables in this study is based on the premise that smart-green agricultural production has not been widely promoted, so the changes in production before and after the whole public participation in smart-green output have yet to be reflected.

Smart green production in agriculture is essential for a transition economy and the world to meet food security and protect the environment. However, the effects of certification, technology innovation, natural resource management, and low pesticides on smart-green agriculture production have yet to be identified. Insights from this study can help governments, policy-makers, and farmers in emerging economies by adapting their strategies within their local contexts.

Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.

Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.

Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.

This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.

The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.

This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

The purpose of this paper is to recognize and prioritize the critical drivers (CDs) essential for establishing a sustainable foxnut supply chain (SFNSC) aligned with the sustainable development goals (SDGs) set forth by the United Nations. The objective is to make a meaningful contribution to the longevity and well-rounded sustainability of the foxnut industry by scrutinizing pivotal factors that endorse triple bottom line (TBL) sustainability aspect throughout the supply chain.

A systematic approach, integrating literature reviews and government reports, identified potential CDs for a sustainable foxnut supply chain. Expert opinions refined the list with the help of fuzzy-Delphi method (FDM), and the final CDs were analyzed with fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) to establish their causal relationships and hierarchical importance.

The study identifies the top three CDs for a SFNSC: “Branding of the product”, “The Global increase in demand” and “Value addition of the foxnut”. Moreover, “Storage infrastructure”, “Mechanized processing” and “Proper transportation facilities” also contribute to the sustainability of the foxnut supply chain.

The results hold significance for various stakeholders in the foxnut industry, encompassing producers, policymakers and researchers. The identified CDs can guide decision-making and resource allocation to improve the sustainability of the foxnut supply chain. The study's framework and methodology can also be applied to other industries to promote sustainable practices and achieve SDGs.

This study enhances understanding of CDs for an SFNSC. FDM and F-DEMATEL techniques analyze causal relationships and rank key factors. The SFNSC model may help other major foxnut producers to become more sustainable.

Is access to finance a constraint for small and medium enterprises (SMEs) development or a result of SMEs constraint? Considering the demand-side of the credit market, this paper aims to assess the effect of nonfinancial services (NFS) on financial access through demand for financing (direct effect) and access to finance (indirect effect).

Using data from a five-year comprehensive entrepreneurship program on a package of technical assistance, the author uses two impact assessment methods: before/after and propensity score matching approaches.

The author found significant changes in business practices for treated SMEs and entrepreneurs since both the number and frequency of good business practices increased for most of the SMEs in the program with a positive turnover effect. Evidence of the positive effects of NFS on demand for financing is found in SMEs but this does not involve more access to finance. Despite positive changes in business practices, small-size entrepreneurs continue to self-exclude for financing.

Different pass-throughs are operating within this “recycling” of entrepreneurial resources over time. The author shows the effectiveness of the knowledge on financing mechanism, financial conditions and government financial support, even if these mechanisms do not seem to lead to a significant improvement in access to finance.

This study aims to investigate the intention to use blockchain technology (BT) in the context of supply chain (SC) operations through an integrated technology adoption framework using two well-known models, the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM). Moreover, the study looked at the direct effect of TAM and UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT.

The study used a quantitative research method, and a structured questionnaire was used to gather primary data. The final sample, drawn using a convenience sampling that consisted of 273 managers from the Jordanian manufacturing sector. Structural equation modeling statistical method was conducted using the Smart PLS program to test hypotheses in the proposed study framework.

The study has provided intriguing results. It found that two UTAUT elements, namely performance expectancy and social influence and one TAM element, namely perceived usefulness, have a significant impact on the attitude toward BT. Besides that, the study found that attitude toward BT significantly mediated the relationship between UTAUT-TAM elements and intention to use BT. The findings revealed that three elements namely performance expectancy, social influence and perceived usefulness have statistical significance on intention to use BT through the mediation of attitude. Finally, there is a direct significant positive relationship between the attitude toward BT and intention to use it.

The study helps decision-makers, South Carolina practitioners and academics recognize the fundamental factors that increase manufacturing firms’ intentions to use blockchain in their SCs. This gives decision-makers a better understanding of why users accept or reject BT, as well as how to improve user acceptability through technological design. Future studies should seek for a bigger sample size and use random sampling techniques. Furthermore, the study should be replicated in other industries or developing countries to validate the findings.

There is a scarcity of studies identifying the factors that increase blockchain adoption intention in SCM and developing countries. This study differs in that it examines BT intention to use in the context of SC using an integrated technology adoption framework that uses two well-known models, UTAUT and TAM, whereas other studies typically use only one model/theory. Moreover, given the importance of attitude in behavior, this study also investigated the effect of TAM-UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT.

The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

This study aims to explore the interrelationships among quality and safety metrics within the Global Food Security Index (GFSI). Its primary objective is to identify key indicators and their respective influences on food security outcomes, thereby enriching comprehension of the intricate dynamics within global food security.

The analysis encompasses data from 113 countries for the year 2022, utilizing Bayesian Belief Network (BBN) models to identify significant drivers of both the GFSI and quality and safety dimensions. This methodological approach enables the examination of probabilistic connections among different indicators, providing a structured framework for investigating the complex dynamics of food security.

The study highlights the critical role of regulatory frameworks, access to clean drinking water, and food safety mechanisms in fostering food security. Key findings reveal that “nutrition monitoring and surveillance” has the highest probability (75%) of achieving a high-performance state, whereas “national dietary guidelines” have the highest probability (41%) of achieving a low-performance state. High GFSI performance is associated with excelling in indicators such as “access to drinking water” and “food safety mechanisms”, while low performance is linked to underperformance in “national dietary guidelines” and “nutrition labeling”. “Protein quality” and “dietary diversity” are identified as the most critical indicators affecting both the GFSI and quality and safety dimensions.

This research operationalizes a probabilistic technique to analyze the interdependencies among quality and safety indicators within the GFSI. By uncovering the probabilistic connections between these indicators, the study enhances understanding of the underlying dynamics that influence food security outcomes. The findings highlight the critical roles of regulatory frameworks, access to clean drinking water, and food safety mechanisms, offering actionable insights that empower policymakers to make evidence-based decisions and allocate resources effectively. Ultimately, this research significantly contributes to the advancement of food security interventions and the achievement of sustainable development goals related to food quality and safety.