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Currently, foresight studies have been adapted to incorporate new techniques based on big data and machine learning (BDML), which has led to new approaches and conceptual changes regarding uncertainty and how to prospect future. The purpose of this study is to explore the effects of BDML on foresight practice and on conceptual changes in uncertainty.

The methodology is twofold: a bibliometric analysis of BDML-supported foresight studies collected from Scopus up to 2021 and a survey analysis with 479 foresight experts to gather opinions and expectations from academics and practitioners related to BDML in foresight studies. These approaches provide a comprehensive understanding of the current landscape and future paths of BDML-supported foresight research, using quantitative analysis of literature and qualitative input from experts in the field, and discuss potential theoretical changes related to uncertainty.

It is still incipient but increasing the number of prospective studies that use BDML techniques, which are often integrated into traditional foresight methodologies. Although it is expected that BDML will boost data analysis, there are concerns regarding possible biased results. Data literacy will be required from the foresight team to leverage the potential and mitigate risks. The article also discusses the extent to which BDML is expected to affect uncertainty, both theoretically and in foresight practice.

This study contributes to the conceptual debate on decision-making under uncertainty and raises public understanding on the opportunities and challenges of using BDML for foresight and decision-making.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Our study centered on activity-based workspaces (ABWs), unassigned open-plan configurations where users’ activities determine the workplace. These workspaces are conceived and shaped by accommodation professionals (APs) like managers and architects and are loaded with their ideas, ideals, norms and values; therefore, they are normative and hegemonic. Previous research has largely failed to consider how APs’ spatial conceptions materialize in the workplace. To address this omission, we adopted a narrative approach to study APs’ impact during the conceptualization stage.

The data were collected via a 10-year at-home ethnographic study at a Dutch university, including observations, interviews, documents and reports. Studying the researchers’ organization allowed for a longitudinal research approach and participative observations. The data focused on the narrative techniques of APs when establishing an ABW.

In introducing ABWs, APs resorted to two principal narrative strategies. Firstly, the ABW concept was lauded as a solution to a host of existing problems. Yet, in the face of shortcomings, lecturers were often blamed.

Despite the considerable influence of APs on both the physical layout of workspaces and the nature of academic labor, there is little insight into their conceptions of the academic workspace. Our research contributes a novel perspective by revealing how APs’ workspace conceptions drive the narratives that underpin the roll-out of ABWs and how they construct narratives of success and failure.

The objective of this study is to determine how biophilic designs in study areas affect the productivity of students at the University of the Witwatersrand. The study also seeks to evaluate study areas at Wits in terms of biophilic design, determine whether biophilic design contributes to the preference of students and their study productivity.

This is a cross sectional study that used a mixed methodology. Five study areas were identified and evaluated in terms of biophilic design. At each study area, nine students participated in an open- and close-ended questionnaire regarding their perceptions on study areas and productivity.

The five study areas scored the following results according to the biophilic test: 29.09%, 34.55%, 36.36%, 80.00% and 85.45%, respectively. The students prefer to study in biophilic study areas as it prompts positive emotions and make them feel rejuvenated and energized. However, there are still students studying in the non-biophilic areas due to convenience or due to the biophilic areas that are noisy and lacks monitoring.

With the small sample size, the generalizability of the findings are limited, but does create a foundation for further research.

Universities can learn from the findings and benefit greatly from many biophilic study areas. This could also encourage architects and interior designers to include biophilic design more so in general buildings/rooms.

Study areas at the University of the Witwatersrand was evaluated in terms of biophilic design, while determining whether biophilic design contributes to the preference of students and study productivity.

This study aims to investigate the satisfaction of farmers with the compensation policy for wildlife-caused damages and its influencing factors, analyze the current situation of satisfaction with the compensation policy among farmers, identify factors significantly affecting satisfaction, and explore ways to optimize the compensation policy and improve the satisfaction of farmers based on the effects of various influencing factors.

The Xishuangbanna National Nature Reserve in Yunnan Province, China, is selected as the research area for the study. Through field interviews, 370 valid questionnaires were collected to obtain relevant data on farmers' satisfaction with the compensation policy for wildlife-caused damages. The Oprobit model is utilized to explore the factors influencing farmer satisfaction and to analyze their underlying reasons.

The study reveals that farmers in the communities surrounding the Xishuangbanna National Nature Reserve generally experience low satisfaction with the compensation policy, particularly concerning satisfaction with compensation amounts, which tends to be dissatisfied on average. Satisfaction with the compensation policy is significantly influenced by individual characteristics and household labor structure, while the degree of human-wildlife conflict, wildlife conservation attitudes and household income structure have insignificant impact. Among individual characteristics, gender, education level, health status, and ethnicity are highly significant. In household labor structure, the number of agricultural laborers, non-agricultural laborers, and household agricultural labor time are highly significant.

Building on the overall satisfaction of farmers with the compensation policy, this study further decomposes policy satisfaction into satisfaction with compensation amounts, coverage, and procedures. It provides more targeted recommendations for enhancing satisfaction with the compensation policy, which can help effectively mitigate human-wildlife conflicts and achieve harmonious coexistence between humans and nature.

The paper aims to enhance the understanding of robust food supply chains (FSC) by exploring the capabilities of various digital technologies and examining their interactions.

This study finding shows that digital technology enhances the resilience of the FSC by improving visibility, traceability and adaptability. This resilience provides a competitive advantage, ultimately enhancing the overall business performance.

In developing countries, inadequate infrastructure, poor Internet connectivity and diverse stakeholder systems pose challenges to implementing advanced digital solutions in the FSC.

This paper is among the first to investigate the impact of digital technology on FSC resilience, exploring visibility, flexibility and collaboration.

This paper aims to use Bayesian network (BN) methodology complemented by machine learning (ML) and what-if analysis to investigate the impact of digital technologies (DT) on logistics service quality (LSQ), employing the service quality (SERVQUAL) framework.

Using a sample of 244 Italian firms, this study estimates the probability distributions associated with both DT and SERVQUAL logistics, as well as their interrelationships. Additionally, BN technique enables the application of ML techniques to uncover hidden relationships, as well as a series of what-if analyses to extract more knowledge.

This study was funded by the European Union—NextGenerationEU, in the framework of the GRINS-Growing Resilient, INclusive and Sustainable project (GRINS PE00000018—CUP B43C22000760006). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them.

This research delves into the influence of DTIE and DTA on SERVQUAL logistics, thereby filling a gap in the existing literature in which no study has explored the intricate relationships between these technologies and SERVQUAL dimensions. Methodologically, we pioneer the integration of BN with ML techniques and what-if analysis, thus exploring innovative techniques to be used in logistics and supply-chain studies.

Adopting adaptive behavior has become a basic measure for farmers because the increasingly severe climate change is affecting agricultural production. Perception is a critical first step in adopting adaptive behaviors. Livelihood resilience represents a farmer's ability to adapt to climate change. Therefore, this article aims to explore the impact of livelihood resilience and climate change perception on the climate change adaptation behavior of farmers in the Qinling Mountains region of China.

In this study, 443 micro-survey data of farmers are obtained through one-on-one interviews with farmers. The Logit model and Poisson regression model are used to empirically examine the impact of farmers' livelihood resilience and climate change perception on their climate change adaptation behaviors.

It was found that 86.68% of farmers adopt adaptive behaviors to reduce the risks of facing climate change. Farmers' perception of extreme weather has a significant positive impact on their adaptive behavior under climate change. The resilience of farmers' livelihoods and their perception of rainfall have a significant positive impact on the intensity of their adaptive behavior under climate change. Climate change adaptation behaviors are also different for farmers with different levels of livelihood resilience.

Based on the results, policy recommendations are proposed to improve farmers' perception of climate change, enhance the sustainability of farmers' adaptive behavior to climate change, strengthen emergency management and infrastructure construction and adjust and upgrade farmers' livelihood models.

Creativity plays a crucial role in interpersonal conflict within organizations, yet little research has explored its antecedents in this context. This study aims to investigate power and gender as the main determinants of creativity in interpersonal conflict within organizational contexts.

Two studies were conducted. The first study involved 226 employees from various organizations (M_age = 39.39, SD = 10.39), whereas the second study used a conflict simulation with 160 participants (M_age = 36.90, SD = 10.45) forming dyads. Both studies investigated the impact of relative power (i.e. having more power than the other person) on creativity in conflict, with a focus on the moderating role of gender. Study 2 also manipulated contextual creativity, which served as an additional moderator in this relationship.

Results largely supported our hypotheses, indicating a positive relationship between relative power and creativity in conflict. Importantly, this relationship was stronger among women. Study 2 further focused on the distinct dimensions of creativity, highlighting differences between idea originality and effectiveness.

The findings hold practical significance for organizational leaders and conflict resolution practitioners, and they further underscore the importance of considering gender dynamics in conflict resolution processes within organizations.

This research contributes novel insights into the understanding of creativity within organizational conflicts, emphasizing the interplay between relative power, gender and creativity. Additionally, the exploration of different dimensions of creativity (i.e. originality and effectiveness) adds depth to existing literature in this area.