Abstract
Fashion influencers are a new phenomenon and profession to which many young individuals may currently aspire; such is its impact in the digital and online world. Hence, the article serves an upcoming group of fashion-influencers-to-be, as well as firms that seek the help of such professionals. This study aimed to test the mediating role of the attitude toward influencers in the relation between, on the one hand, perceived credibility, trustworthiness, perceived expertise, likeability, similarity, familiarity, and attractiveness, and, on the other hand, purchase intention. Path analysis was used to test a conceptual model in which attitude toward influencers mediates the relation between perceived credibility, trustworthiness, perceived expertise, likeability, similarity, familiarity, attractiveness, and purchase intention. Among the seven components, the association between perceived credibility, trustworthiness, perceived expertise, similarity, and familiarity, on the one hand, and purchase intention, on the other, was completely and significantly mediated through attitudes toward influencers. It was found that the attitude toward the influencer determines the purchase intent; this attitude is, in turn, conditioned by the competence, the resemblance, and the proximity that the consumer perceives in the influencer. Thus, to lead the consumer to buy a certain product, influencers must pay attention to perceived credibility, trustworthiness, perceived expertise, similarity, and familiarity with the product (or service).

Abstract
The accumulation of many production units with small capacities and transforming them into a larger entity will make them visible in electricity market. Renewable based virtual power plant (VPP) in this paper is a wide energy management system that incorporates probabilistic wind and solar units, nonrenewable Distributed Generation (DG) units, and dispatchable loads. In an electricity market, a VPP optimizes its operating schedules in order to increase its economic efficiency. However, market uncertainties may influence the VPP's profit. In this paper, modelling the uncertainties is implemented by the proposed Information Gap Decision Theory (IGDT). The mentioned scheduling problem is formulated in three operation modes: risk-neutral, risk-averse and risk-seeker. The risk-neutral mode focuses on optimizing the VPP in the day-ahead market. In the risk-averse mode, the robustness function is used under low market prices. Moreover, in the risk seeker mode, an opportunity function is used under higher market prices towards higher profit results. The proposed model allows the VPP to decide on the scheduling of its components and the optimal bids to the day-ahead market. Another purpose is to investigate the role of the renewable-based VPP in minimizing emission and maximizing profit in a two objective way. The IEEE 18-bus test system is utilized to simulate the proposed problem and analyse the results. The performance of the proposed problem is approved using different scenarios. Simulation results justify the advantages and necessities of the proposed problem.

Abstract
Global climate changes and the increase in average temperatures are some of the major contemporary problems that have not been considered in the context of external factors to increase accident risk. Studies that include climate information as a safety parameter in machine learning models designed to predict the occurrence of accidents are not usual. This study aims to create a dataset with the most relevant climatic elements, to get better predictions. The results will be applied in future studies to correlate with the accident history in a retail sector company to understand its impact on accident risk. The information was collected from the National Oceanic and Atmospheric Administration (NOAA) climate database and computed by a wrapper method to ensure the selection of the most features. The main goal is to retain all the features in the dataset without causing significant negative impacts on the prediction score. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

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Abstract
Based on many years of experience as a management consultant in different industries and corporate structures and cultures, the motivation to use digital transformation in connection with variable corporate goals-such as fluctuating workloads, agile response to customer inquiries, and ecological and economic sustainability-results in a process or a product to be developed that intelligently adapts to market requirements and requires forward-looking leadership. Using an AI-based methodical analysis and synthesis approach, the high consumption of economic and human resources is to be continuously monitored and optimization measures initiated at an early stage. The necessary information technology with its infrastructure and architecture is the starting point to accompany the agility and changeability of corporate goals. Researching the relevant documents begins with writing the panorama or the state of knowledge on the topic. This article is about the IT infrastructure based on the requirements for an architecture and behavior that a versatile, agile company needs to accompany the constantly changing framework conditions of the market. The technology used and the available resources, including the human resources, need to be adapted as early as possible. Data now represent the most valuable asset on Earth and future industrial manufacturing systems must maximize the opportunity of data usage. Low-level data must be transformed to make them useful in supporting intelligent decision-making, for example. Furthermore, future manufacturing systems must be highly productive, adaptable, absent of error, and kind to the environment and to local communities. The all-important design should minimize the waste of material, capital, energy, and media. Herein, we discuss the fulfilling of agile customer requirements involving adaptable and modulated production processes (related to the 'agile manufacturing' and 'digital transformation' perspectives).