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This paper examines why farmers self-select out of formal credit markets even though they need external funds.

We use probit and Bayesian probit estimators to detect the determinants of self-selection behavior based on a primary dataset of 2,212 rice farmers in Vietnam. After that, we use the multinomial probit (MNP) and Bayesian MNP estimators to reveal the impact of relevant factors on the decision to self-select for farmers belonging to each self-selection category.

The probit and Bayesian probit estimators show that the decision to self-select depends on household head age, income per capita, farm size, whether or not to have relatives or friends working for banks, the number of previous borrowings, risks related to natural disasters, diseases, and rice price, and the number of banks with which the farmer has relationships. The MNP and Bayesian MNP estimators give further insights into the decision of farmers to self-select in that determinants of the self-selection behavior depend on the reasons to self-select. In concrete, farm size and the number of previous borrowings mitigate the self-selection of farmers who did not apply for loans due to having access to other preferred sources of credit. The self-selection of farmers not applying for loans because of unfavorable loan terms is conditional on household head age, farming experience, income, farm size, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with. Several factors, including education, income, the distance to the nearest bank, whether or not having relatives or friends working for banks, the number of previous borrowings, risks, and the number of banks the farmer has relationships with, affect the self-selection of farmers not applying for loans because of high borrowing costs. The self-selection of farmers not applying for loans because of complex application procedures depends on income and the number of previous borrowings. Finally, the household head’s age, gender, experience, income, farm size, the amount of trade credit granted, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with are the determinants of the self-selection of farmers not applying for loans because of a fear not being able to repay.

This paper fills the knowledge gap by investigating why farmers self-select out of formal credit markets. It provides evidence of how the farmers’ subjective perceptions of rural credit markets contribute to their self-selection.

This paper shows that demand-side constraints are also vital for farmers’ access to bank credit. Improving credit access via easing supply-side constraints may not increase credit uptake without addressing demand-side factors. Given that finding, it recommends policies to improve access to bank credit for farmers regarding the demand side.

Organization theory seeks to explain how people coordinate their behaviors to achieve common objectives, but it has offered little insight into how organizations emerge from such coordination. Fully understanding entities requires knowing their origins. The purpose of this paper is to draw attention to and to suggest an approach for fortifying a foundational weakness in organization theory: pre-organization theory.

To develop pre-organization theory, this paper employs an evolutionary approach that integrates three theories. This paper first employs memetics to articulate a unit of selection, the i-memeplex, and next introduces inducement-contribution theory to tailor the i-memeplex to pre-organization, yielding a founder’s mental map for exchanges of inducements and contributions. It then applies generalized Darwinism to complete its evolutionary theory of pre-organization.

Memetics, inducement-contribution theory, and generalized Darwinism can be integrated to create a promising theoretical solution, but further investigation is needed to assess the empirical and practical value of pre-organization theory.

This paper contributes to organization theory by (1) explicating a foundational weakness in organization theory – its lack of pre-organization theory – and (2) integrating a novel set of theories to develop an evolutionary theory of pre-organization.

Current reinforcement learning (RL) algorithms are facing issues such as low learning efficiency and poor generalization performance, which significantly limit their practical application in real robots. This paper aims to adopt a hybrid model-based and model-free policy search method with multi-timescale value function tuning, aiming to allow robots to learn complex motion planning skills in multi-goal and multi-constraint environments with a few interactions.

A goal-conditioned model-based and model-free search method with multi-timescale value function tuning is proposed in this paper. First, the authors construct a multi-goal, multi-constrained policy optimization approach that fuses model-based policy optimization with goal-conditioned, model-free learning. Soft constraints on states and controls are applied to ensure fast and stable policy iteration. Second, an uncertainty-aware multi-timescale value function learning method is proposed, which constructs a multi-timescale value function network and adaptively chooses the value function planning timescales according to the value prediction uncertainty. It implicitly reduces the value representation complexity and improves the generalization performance of the policy.

The algorithm enables physical robots to learn generalized skills in real-world environments through a handful of trials. The simulation and experimental results show that the algorithm outperforms other relevant model-based and model-free RL algorithms.

This paper combines goal-conditioned RL and the model predictive path integral method into a unified model-based policy search framework, which improves the learning efficiency and policy optimality of motor skill learning in multi-goal and multi-constrained environments. An uncertainty-aware multi-timescale value function learning and selection method is proposed to overcome long horizon problems, improve optimal policy resolution and therefore enhance the generalization ability of goal-conditioned RL.

This paper critically evaluates potential barriers to employment opportunities for ethnic minority (EM) individuals in Scottish Local Authorities – both in terms of access to job and development opportunities. It provides a fundamental discussion of concepts around race and ethnicity, and the levels of social injustice, with an explicit focus on institutional racialisation, discrimination and segregation. The paper explores organisational approaches towards recruitment, including positive action and workforce development.

This paper adopts a subjectivist (ontology) and interpretivist (epistemology) stance, based on a small-scale, in-depth investigation. The data have been gathered through semi-structured interviews with equality diversity and inclusion (EDI) officers in four Scottish Local Authorities, utilising thematic analysis.

The finding suggests that participating local authorities have a long way to go to ensure the elimination of barriers to employment for EM people. This is largely based on concerns around limitations in the application of positive action and elimination of disadvantages in recruitment and access to career and development opportunities?

The paper aims to contribute by exploring the availability of employment opportunities for EMs through the eyes of EDI Officers in four local authorities. Their thorough understanding, over- and insight into potential equality issues from an employment perspective are invaluable, focussing on more tangible organisational issues and approaches.

Technological advancements have benefited businesses all over the world in how they set up production lines, create new products/services and trade goods. Multinational corporations can communicate instantly with their distant operations by utilizing information technology tools and communication networks. Businesses have taken a significant shift and new factors have emerged which affect company's competitiveness. In case of resorting to an outsourcing option, a comprehensive approach for valuing the essential criteria is often missing. While specifically focusing on the decisions that have a huge impact on company's performance, it is crucial to pay close attention to the ways of selecting suppliers. The purpose of research is to choose the optimal manufacturing alternative from a set of possibilities.

The current research utilizes the Delphi technique for collection of vital criteria such as “quality”, “cost”, “delivery”, “warranties and claims”, “supplier profile”, “relationship and communication” and their respective sub-criteria. The purpose of research is to choose the optimal manufacturing alternative from a set of possibilities. In this regard, Analytical Hierarchy Process (AHP) technique is employed.

The current research enlightens that outsourcing can yield promising beneficial results. The results highlighted that in Hi-tech public sector organizations, international alternative is found best in almost all criteria especially in vital criteria such as “Quality”, “Cost”, “Delivery”, “Supplier Profile,” etc. Similarly, in case the outsourcing is done to a Domestic alternative, still the Domestic alternative is found effective in comparison to in-house manufacturing setups. The research showed unexpected results. Because previously it was assumed that in-house manufacturing would be more beneficial. However, the current findings support the “NASA” strategy which moved toward outsourcing to private sector.

Limitations of the proposed methodology also produce opportunities for further exploration of the topic. One key limitation of the research described in this study is that the parameters and their sub-parameters interdependency were not taken under consideration. This means that quality and cost are not dependent upon each other. However, in reality quality and cost are interlinked. This means if quality is increased, cost is also increased. Similarly, for products having zero percent of re-claim, the product would have to be manufactured with high quality.

The study is advantageous for both suppliers and purchasers, in any type of businesses where decision-making problem are under consideration. This model aids suppliers in revealing, how they can expand their profile, by focusing on the current research's selection criteria. In this way alternatives profile can now be perfected. Moreover, buyers can now rank suppliers on their quality management, financial status and other essential factors in order to conduct purchasing decisions. For the decision maker, the results illustrate which critical factors to evaluate when screening suppliers by applying current model techniques.

It is obvious that nearly almost every industry is forced to look for alternatives for all of its operations if outsourcing is an option. The study's findings have major benefits for all industries with an important role in manufacturing and supply chain operations. These objectives will serve the industries well and they will be able to prioritize their alternative selection criteria based on their operations. The findings of this study can assist any organization in their selection of vendors by providing a more detailed explanation of the impact that various criteria have on the decision-making process.

To the best of authors' knowledge, no previous study has used two approaches (AHP and Delphi study) to propose a model for making manufacturing decisions with domestic, in house and international alternatives in Hi-tech public sector organizations. The model not only benefits the manufacturers for choosing suitable suppliers but also aids suppliers to build their profile in an improved fashion by focusing on the vital attributes. This research benefits managers to improve their ability to make effective purchasing decisions, and also opens new avenues for researchers to further explore such findings in other areas as well.

Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.

To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.

The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.

A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.

The basic unit of the family is the married couple who are brought together through various means, the internet being an additional medium. This study is an attempt to capture changes in the realm of family through a detailed analysis of the matrimonial websites in India from a sociological perspective. With the advent of the internet technology, it explores whether and how the internet as a new medium of spouse selection influences marriage choices and family dynamics during match-fixing. It seeks to unweave the individual–family–community dynamics in the context of changing gender norms. The findings of the study are based on mixed-methods through the use of both qualitative and quantitative data gathered from the website and personal interviews. These data were further strengthened through the walkthrough method and participant observation. The findings of this study reflect upon the prescriptive, restrictive and supportive role played by the family in the context of online spouse selection. It also documents resilience and change (in terms of family structure and norms) in the realm of the family in the context of changing matrimonial preferences.

Electronic devices aid communication during new communication phases and the scope of cognitive radio networks has changed communication paradigms through efficient use of spectrums. The communication prototype of cognitive radio networks defines user roles as primary user and secondary user in the context of the spectrum allocation and use. The users who have licensed authority of the spectrum are denoted as primary users, while other eligible users who access the corresponding spectrum are secondary users.

The multiple factors of transmission service quality can have a negative influence due to improper scheduling of spectrum bands between primary users and secondary users. There are considerable contributions in contemporary literature concerning spectrum band scheduling under spectrum sensing. However, the majority of the scheduling models are intended to manage a limited number of transmission service quality factors. Moreover, these service quality factors are functional and derived algorithmically from the current corresponding spectrum. However, there is evidence of credible performance deficiency regarding contemporary spectrum sensing methods

This article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

This article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

Drawing on media richness theory and a framework of interpersonal communication goals, this study investigates how and why the IT industry's top managers use communication media to achieve their interaction goals in e-leadership.

A qualitative research approach is applied to understand top managers' communication media use and interaction goals. The empirical data were gathered through semi-structured interviews with 33 top managers from large IT companies and analysed using theory-guided thematic and ideal-type analyses.

Top managers were categorized into three types, based on their communication goals through face-to-face communication. Relationship-oriented top managers pursued relational and communal goals, whereas task-oriented ones wished to achieve instrumental and communal goals. Task- and relationship-oriented top managers pursued relational, instrumental, and communal goals. This study indicates that communal, instrumental, relational, and self-presentational goals influence managers' communication media selection.

This study brings new knowledge to the management communication research field. It expands the framework of interpersonal communication goals by identifying communal goals as a new category, in addition to existing instrumental, relational and self-presentational goals. This study suggests that media richness theory could be advanced by recognizing that a broader set of communication goals – including communal, instrumental, relational, and self-presentational – influences managers' communication media selection.

Universities in the United Kingdom, like their counterparts globally, are confronting difficulties associated with the well-being of students. The origins of these challenges are complex, exacerbated by various global events. In response, universities are trying to address these growing concerns and the escalating need for student support. Faculty members are often recruited to assist students in navigating academic and personal challenges. The aim of this study was to investigate how the process of student mentoring, by faculty members, could be made more operationally robust to better support student demand, thus yielding greater value for both students and staff.

A qualitative approach was adopted with 19 academic faculty working as mentors within a UK business school who participated in 90-minute semi-structured interviews. Interviews were analysed using an operational (transformation) management framework, with findings categorised under three key headings – inputs, transformations and outputs – to discover how the operational process of mentoring students could be enhanced.

Participants discussed the inputs required to deliver mentoring, the process of transformation and their desired outputs. Findings suggest coordinated and relevant inputs that is, information, environments and technology, coupled with good mentor selection and recruitment improves operational robustness, adding greater value to the student experience by creating more purposeful outputs, thereby benefiting themselves and their students.

The application of an operational (transformation) process framework to analyse faculty mentoring of students is unique, thereby offering new insights into the construction and management of these types of academic support initiatives.