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The study aims to demonstrate that farmers' markets can represent a model of environmental, social and governance reference for modern agri-food systems facing the challenge of post COVID-19 pandemic reconstruction, responding to consumer expectations in terms of health, safety and wholesomeness of agri-food products.

A sample of consumers was surveyed in farmers' markets and social network analysis (SNA) was adopted as a methodological approach to reconstruct the links between the worlds of production and consumption and to derive the relative importance attributed to various factors that promote relational structures.

The work demonstrates the importance of sustainability – as a productive and behavioural model of firms – for the construction of efficient and durable relationship systems in two farmer markets in Sicily. In particular, four fundamental components emerge in the construction of networks represented by consumer sensitivity to sustainability processes, the individual behavioural model of purchasing and consumption, the expectation of political direction and the level and factors of knowledge of the firm. The clustering elements of the relationships were found to be the territory and local products, the environmentalist attitude and the protection of resources, as well as the adoption of a rational waste disposal policy, the fight against food waste, the encouragement of healthier and more sustainable consumption styles, clear and transparent communication and the activation of sustainable supply chain processes in line with the Sustainable Development Goals (SDGs).

The paper aims to demonstrate how alternative food systems can become a useful model for large enterprises, which are committed to rebuilding their business strategy to overcome the current crisis.

Destinations to be able to compete with each other need to equip themselves with as many competitive advantages as possible. Tourists' loyalty to a destination is considered as a prominent competitive tool for destinations. Tourists' loyalty manifests itself in recommendation of the destination to others, repeat visit of the destination and willingness to revisit the destination. Although a plethora of studies have tried to define models to show the relation between loyalty and the antecedent factors leading up to it, few of them have tried to integrate these models with mathematical approaches for better understanding of loyalty behavior. The purpose of this paper is to integrate a tourist destination model with Bayesian Network in order to predict the behaviour of destination loyalty and its antecedent factors.

This paper has developed a probability model by the integration of a destination loyalty model with a Bayesian network (BN) which enables to predict and analyze the behavior of loyalty and its influential factors. To demonstrate the application of this framework, Tehran, the capital of Iran, was chosen as a destination case study.

The outcome of this research will assist in identifying the weak key points in the tourist destination area for giving insights to the marketers, businesses and policy makers for making better decisions related to destination loyalty. In the analysis process, the most influential factors were recognized as the travel environment image, natural/historical attractions and, with a lower degree, infrastructure image which help the decision maker to detect and reinforce the weak factors and put more effort in focusing on improving the necessary parts rather than the irrelevant parts.

The research identified all critical factors that have the most influence on destination loyalty while driving the associate uncertainty which is significant for the tourism industry. This resulted in better decision-making which is used to identify the impact of tourism destination loyalty.

Studies about product customization decision are especially relevant for organizations that decide opening a subsidiary overseas. This scenario requires the company to decide which products should be customized and which products should be standardized when selling products in international markets. The main purpose of this paper is to identify which factors influence the decisions on the customization of industrial products and consumer products to a particular country in the marketing function of a global company.

To do so, a literature review was conducted addressing the following topics: internationalization, international marketing and product customization factors. With regard to methodological aspects, an initial qualitative phase was conducted with four exploratory case studies. In the quantitative phase, an online survey was developed, obtaining 123 records of an intentional non-probabilistic sample.

As a result, six factors were deemed essential to the product customization decision: customers’ characteristics, sustainable return on investment, sustainable profit, legal requirements, sales of other products in the portfolio and weather differences.

The authors expect that the results of this research contribute academically for the management knowledge about the meanings that product customization can assume in internationalized companies, and, additionally, in a business way, the authors expect that they help companies make strategic decisions on the appropriate measure to take regarding product customization in international markets, whether industrial products or consumer products. With these findings, the authors expect to make a valid contribution about product customization decision and suggesting future studies from other perspectives.

The purpose of this paper is to explain the issues and variables that influence the bureaucracy’s role and work in the transitional period, which is known with its complexity, uncertainty, instability, ambiguity and asymmetry. This paper highlights the transition from theoretical perspective, giving examples from the Polish experience in transition.

This paper describes the changing roles of public bureaucracies in transitional periods by highlighting their ecology with the transitional period and analyzing the determinants of bureaucracy’s role and functions in terms of participation in policy-making policies, providing consultations to executives and elected officials, working as a mediator in communication and acting as an active participant in the development process giving examples from Poland. Finally, it highlights the way the bureaucracy manages its functions and the internal and external variables that constitute various levels affecting this role in the transition.

Bureaucracy is supposed to function naturally and stably in an unstable environment (transition) as its success in doing these functions and helping the new regime to exceed the transition and achieve its goals depends on many variables (bureaucracy capabilities and skills, history, power, experience, the nature of politics and bureaucratic functions, political support, policy environment, knowledge, cohesion, etc.). Most of these variables were demonstrative in the case of Poland.

This paper will be useful for scholars and policymakers interested in public administration role in the time of transition, especially countries that recently have been experiencing the transition.

The purpose of this paper is to investigate the role of universities in preparing disabled students to become entrepreneurially inclined after graduation with the aim of developing an entrepreneurial inclination (EI) model.

A cross-sectional survey was employed using 220 disabled universities’ students in the north-central Nigeria. Data were analyzed using descriptive statistics, correlation analysis and structural equation model. All analyses were performed using SPSS version 22 and AMOS version 22.

The findings buttress the significant position of universities in promotion entrepreneurial spirit. It revealed that the university’s role (UR), entrepreneurship education (EE) and role models (RMs) have a positive influence on disabled students’ EI. Universities that make provisions for entrepreneurship infrastructure, knowledge and RMs to disabled students will boost their EI. Second, the more lecturers and RMs inspire students, method of teaching and demonstrating enthusiasm are applied in the teaching of entrepreneurship, the better it prepares students for entrepreneurial career after graduation.

The study is only restricted to Federal Universities in the North-Central Nigeria. Further research could be conducted to cover other tertiary institutions in North-Central Nigeria. Furthermore, the study employed the cross-sectional approach. A longitudinal approach should be employed to study the trend over a period of at least two years. Finally, the factors identified in triggering EI may not be sufficient enough in explaining the phenomenon. There are other factors that may contribute in influencing EI of the disabled students that were not part of this study.

This study indicates a number of implications for the universities and policy makers. Specifically, EE, UR and RMs make significant contributions to inclination for disabled students. These factors are key for universities in Nigeria to consider in preparing these students to become entrepreneurial graduates. Policy makers and other stakeholders need to develop keen interest in designing entrepreneurship curriculum to accommodate the specific needs of students with disabilities.

This study is the first in Nigeria to empirically test the relationship between UR, EE and EI as well as the moderating effect of RMs among universities’ disabled students.

The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.

First, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.

The experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.

This method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.

The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.

The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.

Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.

This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.

This paper aims to describe the “InDO: Institute Demographic Ontology” and demonstrates the InDO-based semiautomated process for both generating and extending a knowledge graph to provide a comprehensive resource for marginalized US graduate students. The knowledge graph currently consists of instances related to the semistructured National Science Foundation Survey of Earned Doctorates (NSF SED) 2019 analysis report data tables. These tables contain summary statistics of an institute’s doctoral recipients based on a variety of demographics. Incorporating institute Wikidata links ultimately produces a table of unique, clearly readable data.

The authors use a customized semantic extract transform and loader (SETLr) script to ingest data from 2019 US doctoral-granting institute tables and preprocessed NSF SED Tables 1, 3, 4 and 9. The generated InDO knowledge graph is evaluated using two methods. First, the authors compare competency questions’ sparql results from both the semiautomatically and manually generated graphs. Second, the authors expand the questions to provide a better picture of an institute’s doctoral-recipient demographics within study fields.

With some preprocessing and restructuring of the NSF SED highly interlinked tables into a more parsable format, one can build the required knowledge graph using a semiautomated process.

The InDO knowledge graph allows the integration of US doctoral-granting institutes demographic data based on NSF SED data tables and presentation in machine-readable form using a new semiautomated methodology.

As a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.

Six phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.

From their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.

A refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.