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The COVID-19 pandemic has engendered changes in previously unimaginable timeframes, leading to new ways of working, which can quickly become the “ordinary” way of working. Many traditional workplace and educational practices and environments, however, are disadvantageous to people with disability and consequently are under-represented in the workforce and higher education.

Contributing factors include exclusionary societal and employer attitudes and inaccessible built environments including lack of attention to paths of travel, amenities, acoustics, lighting and temperature. Social exclusion resulting from lack of access to meaningful work is also problematic. COVID-19 has accelerated the incidence of working and studying from home, but the home environment of many people with disability may not be suitable in terms of space, privacy, technology access and connection to the wider community.

However, remote and flexible working arrangements may hold opportunities for enhancing work participation of people with disabilities. Instigating systemic conditions that will empower people with disability to take full advantage of ordinary working trajectories is key. As the current global experiment in modified work and study practices has shown, structural, organisational and design norms need to change. The future of work and study is almost certainly more work and study from home. An expanded understanding of people with disabilities lived experience of the built environment encompassing opportunities for work, study and socialisation from home and the neighbourhood would more closely align with the UNCRPD's emphasis on full citizenship.

This paper examines what is currently missing in the development of a distributed work and study place continuum that includes traditional workplaces and campuses, local neighbourhood hubs and homes.

In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.

The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.

The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.

This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).

This study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.

A fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.

The effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.

The outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.

Big data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.