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Racial stigma and racial criminalization have been centralizing pillars of the construction of Blackness in the United States. Taking such systemic injustice and racism as a given, then question then becomes how these macro-level arrangements are reflected in micro-level processes. This work uses radical interactionism and stigma theory to explore the potential implications for racialized identity construction and the development of “criminalized subjectivity” among Black undergraduate students at a predominately white university in the Midwest. I use semistructured interviews to explore the implications of racial stigma and criminalization on micro-level identity construction and how understandings of these issues can change across space and over the course of one's life. Findings demonstrate that Black university students are keenly aware of this particular stigma and its consequences in increasingly complex ways from the time they are school-aged children. They were aware of this stigma as a social fact but did not internalize it as a true reflection of themselves; said internalization was thwarted through strong self-concept and racial socialization. This increasingly complex awareness is also informed by an intersectional lens for some interviewees. I argue not only that the concept of stigma must be explicitly placed within these larger systems but also that understanding and identity-building are both rooted in ever-evolving processes of interaction and meaning-making. This research contributes to scholarship that applies a critical lens to Goffmanian stigma rooted in Black sociology and criminology and from the perspectives of the stigmatized themselves.

This paper aims to offer an approach to cyborg composing with artificial intelligence (AI). The author posits that the hybridity of the cyborg, which amalgamates human and artificial elements, invites a cascade of creative and emancipatory possibilities. The author critically examines the biases embedded in AI systems while gesturing toward the generative potential of AI–human entanglements. Drawing on Bakhtinian theories of dialogism, the author contends that crafting found poetry with AI could inspire writers to problematize the ideologies embedded into the corpus while teasing apart its elisions or contradictions, sparking new forms of expression at the interface of the organic and the artificial.

To illustrate this approach to human–AI composing, the author shares a found poem that she wrote using ChatGPT alongside her reflection on the poem. The author reflects on her positionality as well as the positionality of her artificial interlocutor, interrogating the notion of subjectivity in relation to Bakhtinian dialogism and multivocality.

Weaving tales of resilience in harmony or tension with AI could unravel threads of possibility as human writers enrich, deepen or complicate AI-generated texts. By composing with AI, writers can resist closure, infiltrate illusions of objectivity and “speak back” to AI and the dominant voices replicated in its systems.

By encouraging students to critically engage with, question and complicate AI-generated texts, one can open avenues for alternative ways of thinking and writing, inspiring students to imagine and compose speculative futures. Ultimately, in animating assemblages of the organic and the artificial, one can invite transformative possibilities of being and becoming.

Present study aimed to integrate Geographic Information Systems (GIS) and Building Information Modeling (BIM) in conjunction with multicriteria decision-making (MCDM) to enhance infrastructure investment planning.

This analysis combines GIS databases with BIM simulations for a novel highway project. Around 150 potential alternatives were simulated, narrowed to 25 more effective routes and 3 options underwent in-depth analysis using PROMETHEE method for decision-making, based on environmental, cost and safety criteria, allowing for comprehensive cross-perspective comparisons.

A comprehensive framework proposed was validated through a case study. Demonstrating its adaptability with customizable parameters. It aids decision-making, cost estimation, environmental impact analysis and outcome prediction. Considering these critical factors, this study holds the potential to advance new techniques for assessment and planning railways, power lines, gas and water.

The study acknowledges limitations in GIS data quality, particularly in underdeveloped areas or regions with limited technology access. It also overlooks other pertinent variables, like social, economic, political and cultural issues. Thus, conclusions from these simulations may not entirely represent reality or diverse potential scenarios.

The proposed method automates decision-making, reducing subjectivity, aids in selecting effective alternatives and considers environmental criteria to mitigate negative impacts. Additionally, it minimizes costs and risks while demonstrating adaptability for assessing diverse infrastructures.

By integrating GIS and BIM data to support a MCDM workflow, this study proposes to fill the existing research gap in decision-making prioritization and mitigate subjective biases.

The aim of this paper was to study current practices in FM work order processing to support and improve decision-making. Processing and prioritizing work orders constitute a critical part of facilities and maintenance management practices given the large amount of work orders submitted daily. User-driven approaches (UDAs) are currently more prevalent for processing and prioritizing work orders but have challenges including inconsistency and subjectivity. Data-driven approaches can provide an advantage over user-driven ones in work-order processing; however, specific data requirements need to be identified to collect and process the functional data needed while achieving more consistent and accurate results.

This paper presents the findings of an online survey conducted with facility management (FM) experts who are directly or indirectly involved in processing work orders in building maintenance.

The findings reflect the current practices of 71 survey participants on data requirements, criteria selection, rankings, with current shortcomings and challenges in prioritizing work orders. In addition, differences between criteria and their ranking within participants’ experience, facility types and facility sizes are investigated. The findings of the study provide a snapshot of the current practices in FM work order processing, which aids in developing a comprehensive framework to support data-driven decision-making and address the challenges with UDAs.

Although previous studies have explored the use of selected criteria for processing and prioritizing work orders, this paper investigated a comprehensive list of criteria used by various facilities for processing work orders. Furthermore, previous studies are focused on the processing and prioritization stage, whereas this paper explored the data collected following the completion of the maintenance tasks and the benefits it can provide for processing future work orders. In addition, previous studies have focused on one specific stage of work order processing, whereas this paper investigated the common data between different stages of work order processing for enhanced FM.

This paper compares traditional and digital banks in nine categories of complaints and provides insights to improve complaint management performance.

A sample of the major Brazilian banks was defined, with four traditional and four digital banks. The grey relational analysis (GRA) method was applied as an analytical tool to compare the most frequent complaints of traditional and digital banks. The most critical complaints identified were considered to discuss potential improvements in complaint management using quality and service management system concepts.

The GRA method enabled the development of a ranking of nine complaint categories, considering the uncertainty involved in the data and differentiating between traditional and digital banks. The most critical complaint categories, regardless of business model, were “unauthorized charges” and “poor service,” which were ranked first and second in the frequency rankings. Traditional and digital banks differed the most in the complaint category “unfair charge,” ranking third and eighth in the rankings, respectively.

Managers from traditional and digital banks can improve complaint management performance by applying ISO 9001 and ISO 20000 concepts such as incident, problem, change, service level, availability, capacity, information technology service continuity and financial management.

The study's findings can help bank managers improve service levels in the face of technological competition. Improving these organizations is an important factor for developing countries such as Brazil.

This paper reveals the differences between two business models regarding complaint management. It also considers a methodological approach to include the uncertainty related to customers' perception and subjectivity inherent to complaints.

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

The purpose of this study is to ascertain how cluster organisations have been fostering green transformation in Poland.

This paper adopts a multiple case study approach. Data collection methods involved in-depth interviews with cluster organisation managers and researchers to identify support measures for green transformation and to investigate the factors influencing their actions as well as a comprehensive analysis of documents, including cluster organisations‘ strategies.

Cluster organisations manage and participate in actions that create favourable conditions for pursuing low-carbon and circular economy ventures. They not only assist their members in overcoming obstacles related to green transformation but also engage non-members – which can lead to spillovers reaching beyond their borders. Their engagement takes place across all phases of the green transformation process.

For various reasons, the research was designed as qualitative to understand the opinions and experiences of various actors engaged in green transformation within cluster organisations’ ecosystems. The key factor influencing this decision stems from the fact that knowledge of the involvement of cluster organisations in supporting green transformation still needs to be completed and scattered. The limitations of the study include limited access to information and the fact that qualitative research allows for a certain amount of subjectivity, and the results should be generalised carefully. Moreover, the interviews were carried out with a non-random sample of participants. Another limitation of the study is related to biased views, which could have been shared by interviewees acting as representatives of the studied cluster organisations.

Cluster organisations have emerged as drivers of circular transition by promoting sustainable practices such as material recycling, biological recovery and parts harvesting. These initiatives contribute to reducing waste, conserving resources, and minimising the environmental footprint of industries. These organisations can be active agents of transformation, orchestrating collaborative efforts that have a far-reaching impact on industries and economies.

This is one of the first and most comprehensive studies on the role of cluster organisations in Poland in supporting green transformation. This paper identifies and systematises the actions undertaken to provide a clear understanding of the internal processes within cluster organisations.

This study builds on previous theoretical work that considered artificial intelligence (AI) and its potential for creating “teacher-centaurs” whose labor could be accelerated through the use of generative AI (Fassbender, in review). The purpose of this paper is to use empirical methods to study centaur teachers and the division of labor (Durkheim, 1893/2013) that arise from outsourcing teaching tasks to AI.

Multiple case study (Stake, 2006) was used to collect data on two secondary English teachers who were early adopters of generative AI. Data included semi-structured interviews as well as ChatGPT chat logs, which helped in describing how teaching approaches evolved using AI technology.

Results showed that teachers used AI for planning, instruction and assessment. AI-augmented teaching practices allowed teachers to complete tasks with greater speed, which in turn increased stamina and short-term work–life balance. Given the novelty of AI, concerns about data privacy and academic integrity raised ethical questions.

ChatGPT’s rise to popularity in 2023 brought with it significant discussions about education, specifically how students would use AI primarily as a tool for plagiarism. This study takes a different focus, considering how early adoption of AI has begun changing teacher labor, offering implications for the future of the teaching profession.

Emphasizing the increasing need for social presence in interpersonal interactions and the irreplaceable aspects of face-to-face communications, this study aims to explore the emotional impact of interpersonal influence on consumers after purchase. As individuals respond differently to others’ feedback (positive and negative/verbal and nonverbal), the author investigates potential moderating factors of the impact of feedback on consumer’s emotions in a postpurchase context.

A qualitative study was conducted using the method of semistructured individual interviews to collect data. The author selected a heterogeneous group of 30 consumers belonging to two categories: 13 adults (including seven women and six men) and 17 adolescents (including eight girls and nine boys). The author took into account this type of sampling in the selection of respondents, as investigating the influence of the respondent’s gender is one of the research objectives.

The thematic content analysis method released a set of propositions the author suggests for future validation: five moderating factors the author established from the literature review (strength of social ties, level of expertise, type of the product and consumer’s age and gender), while four factors sprang from the collected data (consumer’s level of conviction, repetition of the feedback, the feedback’s argumentation and its level of discretion).

The subjectivity of the interviewees’ personal descriptions of their felt internal states affects the accuracy of their responses. In addition, the psychological aspect of the study provoked reluctance and discretion from some respondents. Further research studies could target these limitations to study each identified moderating factor separately and search for the secondary variables that tend to be linked to these factors (e.g. the expertise level is linked to personality variables, such as the perceived level of self-confidence). Furthermore, subsequent studies can go beyond the affective impact of feedback and investigate the behavioral aspect (repurchase intentions).

This study is of great importance in providing more explanations for the reasons why consumers repurchase or abandon a product. The importance of the emotional power of others’ feedback suggests that, when positioning their offers, marketers must ensure that their product has a strong chance of acceptance by consumer’s significant other. In addition, companies must argue their offers, allowing consumers to increase their knowledge about the product. Moreover, interpersonal cues and expertise level are more important competences to find in employees. Who is more than a vendor, for example, to be perceived as having a high level of expertise in his field?

This study stresses the importance of face-to-face interpersonal interaction in a time when social lives are submerged by social media and virtual communications. The findings suggest that offline social power still matters, and its impact is relative to multiple factors that count for consumers. Face-to-face interaction has been viewed as the most efficient way to satisfy individuals’ social needs for connectedness.

This paper provides new insights into the impact of offline interpersonal verbal and nonverbal feedbacks. The feedback-affect process within consumers was explored, and the postpurchase context was precisely emphasized.