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Digital technologies, and the affordances they provide, can shape institutional processes in significant ways. In the last decade, social media and other digital platforms have redefined civic engagement by enabling new ways of connecting, collaborating, and mobilizing. In this article, we examine how technological affordances can both enable and hinder institutional processes through visibilization – which we define as the enactment of technological features to foreground and give voice to particular perspectives and discourses while silencing others. We study such dynamics by examining #SchauHin, an activist campaign initiated in Germany to shine a spotlight on experiences of daily racism. Our findings show how actors and counter-actors differentially leveraged the technological features of two digital platforms to shape the campaign. Our study has implications for understanding the role of digital technologies in institutional processes as well as the interplay between affordances and visibility in efforts to deinstitutionalize discriminatory practices and institutions.

Physical stores are increasingly dependent on impulse visits and the impulse purchases of passers-by. Interactive advertising screens in store windows could help retailers increase impulse-visit urges and impulse-buying urges. However, the effects of interactive screens in physical surroundings have not been studied before. Therefore, this study aimed to examine the effect of interactive screens on impulse urges and gain insight into the underlying mechanism that explains the possible effect.

An interactive screen was placed in a store window. Using three field experiments, we studied the effect of interactivity-level (high vs low) on the impulse-visit and impulse-buying urges of passers-by, and the mediating role of self-agency in these effects.

Highly interactive (compared to less interactive) advertising screens in store windows positively affect impulse-visit and impulse-buying urges through self-agency. Retailers can therefore use interactive advertising screens to increase the number of impulse purchases if feelings of self-agency are activated.

This is the first study to examine the extent to which interactive screens in a store window enhance the impulse-visit and impulse-buying urges of passers-by and the mediating factor of these effects. By conducting three field experiments, we achieved a high external validity and managed to share very reliable results owing to the replication of the findings.

Surveillance is the emerging concept in the current technology, as it plays a vital role in monitoring keen activities at the nooks and corner of the world. Among which moving object identifying and tracking by means of computer vision techniques is the major part in surveillance. If we consider moving object detection in video analysis is the initial step among the various computer applications. The main drawbacks of the existing object tracking method is a time-consuming approach if the video contains a high volume of information. There arise certain issues in choosing the optimum tracking technique for this huge volume of data. Further, the situation becomes worse when the tracked object varies orientation over time and also it is difficult to predict multiple objects at the same time. In order to overcome these issues here, we have intended to propose an effective method for object detection and movement tracking. In this paper, we proposed robust video object detection and tracking technique. The proposed technique is divided into three phases namely detection phase, tracking phase and evaluation phase in which detection phase contains Foreground segmentation and Noise reduction. Mixture of Adaptive Gaussian (MoAG) model is proposed to achieve the efficient foreground segmentation. In addition to it the fuzzy morphological filter model is implemented for removing the noise present in the foreground segmented frames. Moving object tracking is achieved by the blob detection which comes under tracking phase. Finally, the evaluation phase has feature extraction and classification. Texture based and quality based features are extracted from the processed frames which is given for classification. For classification we are using J48 ie, decision tree based classifier. The performance of the proposed technique is analyzed with existing techniques k-NN and MLP in terms of precision, recall, f-measure and ROC.

The present study focused on examining the effect of treated wastewater (TWW) on soil chemical properties. Also, efforts were made to compare the soil chemical properties under TWW irrigation with that under groundwater (GW).

During the years 2021 and 2022, surface and subsurface soil samples were randomly collected in triplicate by using an auger fortnightly at two depths (20 and 40 cm) from the selected spot areas to represent the different types of irrigation water sources: TWW and GW. Samples of the GW and the TWW were collected for analysis.

This study examines the impact of TWW on soil characteristics and the surrounding environment. TWW use enhances soil organic matter, nutrient availability and salt redistribution, while reducing calcium carbonate accumulation in the topsoil. However, it negatively affects soil pH, electrical conductivity and sodium adsorption ratio, although remaining within acceptable limits. Generally, irrigating with TWW improves most soil chemical properties compared to GW.

In general, almost all of the soil’s chemical properties were improved by irrigating with TWW rather than GW. Following that, wastewater is used to irrigate the soil. Additionally, the application of gypsum to control the K/Na and Ca/Na ratios should be considered under long-term TWW and GW usage in this study area in order to control the salt accumulation as well as prevent soil conversion to saline-sodic soil in the future. However, more research is needed to thoroughly investigate the long-term effects of using TWW on soil properties as well as heavy metal accumulation in soil.

The purpose of this paper is to examine millennial customer perceptions of food trucks and to identify factors that can foster their behavioral intentions pertaining to food trucks.

The study is based on a sample of 247 millennial customers of various food truck vendors in the United States and was assessed using ordinary least squares regression analysis.

Food truck image and employee friendliness were found to impact both customer satisfaction and word of mouth behavior; however, the other hypotheses were not supported.

There were two limitations. The first was that one of the constructs did not achieve the minimum average variance extracted. The second was that data collection was done in a single city in the United States; therefore, future research could overcome these limitations through a refinement of the construct’s items and targeting more cities.

There has been limited academic research on the millennial customer perceptions of the food truck phenomenon. This research addresses that gap through a field study that examines factors that contributed to the growth and popularity of food trucks among millennials

The purpose of this paper is to propose a model of the Islamic sovereign wealth funds (ISWFs) based on Islamic finance principles to modify the precarious image of SWFs from Muslim countries. The Shariah laws are the cardinal direction for this study.

The authors applied a qualitative research technique that consists of three approaches: exploratory case study approach to critically examine and rank the existing status of SWFs; descriptive analysis; and content analysis to present a model of ISWFs in comparison of conventional SWFs.

The authors propose a model of the “Islamic Sovereign Wealth Funds” based on four key pillars: the major Shariah principles; the Islamic corporate governance framework; the Islamic transparency and disclosure framework; and the Islamic corporate social responsibility framework. Furthermore, the authors argue that the potential effect of the ISWFs on Islamic finance and economy will be positive.

The model is an initial work and idea to convert SWFs from Muslim countries into ISWFs, which required an in-depth policy review by governments.

The findings of the paper are useful for policymakers and governments of the Muslim countries to overcome the issues and criticism on SWFs by converting them in ISWFs.

This paper contributes to the literature related to Islamic finance and sovereign wealth fund by presenting a first model of ISWFs for Muslim countries.

A series of “learning lab” projects on disaster risk management for sustainable development (DRM-SD) have been accomplished from 2014 to 2016 in Malaysia, Vietnam, Lao PDR and Cambodia by the Centre for Global Sustainability Studies. The project is designed for professionals from the disaster risk management field to encourage integration of sustainable development (SD) concerns into the larger planning framework for DRM. As a case study for capacity building (CB) evaluation, the central purpose of this study is to explore the approaches, feedbacks and implications of the DRM-SD CB project that have been developed and carried out.

Three methods have been used which are participation observations, surveys and document analysis. The results show that the project had successfully applied seven different tools to enhance analytical skills and professional knowledge of development practitioners in specific areas of DRM-SD.

Based on the survey, the project received positive response and valuable information from participants for future project development. Regarding the perspective of outcomes, the result indicates that south–south, ASEAN regional and triangular cooperation and role of higher education in DRM-SD are significant impacts from this project which can bring several benefits and should be promoted as an approach for the DRM-CB project as a whole.

It is hoped that this study will serve as a transfer learning initiative to provide approach guidelines and innovative mechanisms for DRM practitioners who will have the know-how and potential for leadership in DRM-SD.

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.