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Purpose – The purpose of this study is to analyze and design a virtual collaboration information system of the Jamu supply chain network based on a fair adaptive contract to respond to stability challenges in business with an uncertainty environment condition.

Design/Methodology/Approach – System entity approach is used for the purpose of system analysis and then case, sequence diagram, class diagram, graph data modeling, and business process modeling and Notation verse 2 (BPMN2.0) are also used to design the system concept. Each process of the connecting event and gateways was arranged with relevant multicriteria decision approach, whilst an adaptive quantitative formulation based on prescriptive analytics was embedded to ensure a fair contract implementation during the terms for all sphere roles in supply chain.

Findings – The results and implications of this model emphasizes on the knowledge, competence, trust, and fair (KCTF) for actors’ adoption to improve supply chain stability and implementation.

Practical Implications – This led actors to collaborate their business in a more effective way.

Originality/Value – This model can reach more stability in the uncertainty environment.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Purpose – The purpose of this research is to study the ecological developments that are growing rapidly and are complemented by technological developments that make ecology a discipline which is able to collaborate, integrate, and use data for the development of science.

Design/Methodology/Approach – The method involves integration, analysis, and conclusion, drawing knowledge dissemination from heterogeneous ecological data that make the ecological research so complex requiring an approach to simplify the problem.

Findings – The data involved in ecology are very complex and diverse and spread from various sources, which are not mutually integrated so that a structured arrangement is required through the arrangement of computer-based data management.

Research Limitations/Implications – Eco-informatics is one of the options to manage the data, settings, and transform it into information and knowledge.

Purpose – The purpose of this study is to explore the concept of the economic lot sizing and the time cycle period of reordering. The stochastic demand is quite common in the real environment of a cement retailer. The study compares three methods to obtain the optimal solution of a lot-sizing ordering from the real case of the previous study where the dataset is collected from the area of some retailers at Banda Aceh Province of Indonesia.

Design/Methodology/Approach – The problem model appears when the retailer with shortage has to fulfill the lot size in the optimal condition to the stochastic demand while at the same time has the backlog condition. Moreover, when the backorder needs the time horizon for replenishment where this condition influences the holding cost at the store, many retailers try to solve this problem to minimize the holding cost, but on the other side, it should fulfill the customer demand. Three methods are explored to identify that condition: a Wagner–Whitin algorithm, the Silver–Meal heuristic, and the holding and ordering costs. The three methods are applied to the lot sizing when there is a backlog.

Findings – The results of this study show that the Wagner–Whitin algorithm outperforms the other two methods. It shows that the performance increases around 27% when compared to the two other methods in this study.

Research Limitations/Implications – All models are almost approximate and useful to determine the cycle period on stochastic demand.

Practical Implications – The calculation of the dataset with the three methods would give the simple example to the retailer when he faces the uncertainty demand models. The prediction of the calculation is done accurately than the constant calculation, which is more economic.

Social Implications – The calculation will contribute to much better predictions in many cases of uncertainty.

Originality/Value – This is a initial comparative model among other methods to achieve the optimal stock and order for a retailer

Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.

This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.

Videos of police abuse are often spread through technology, raising questions around how perceptions of police are impacted by these images, especially for 18–24-year-olds who are constantly “logged on.” Limited research investigates the impact of social media on attitudes toward police accounting for age and race. The present study utilizes 19 in-depth interviews with a diverse sample of urban college students who regularly use social media in order to understand how they have been impacted by this content. The findings suggest the necessity of using an intersectional framework to understand the impact of tech-witnessed violence. While no gender differences were uncovered, racial differences did surface. White participants described being minimally influenced by videos of police misconduct, rationalizing it as a “few bad apples.” In contrast, participants of color, except those with family members in law enforcement, described being negatively impacted. Viral content contributed to negative opinions of police, emotional distress, and fears of victimization. Ultimately, videos of police brutality do not impact young populations equally. Instead, they are comparatively more harmful to young people of color who spend more time on social media, can envision themselves as the victims, and experience feelings of fear, despair, and anger after watching these videos.