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This study aims to examine the relationship between supportive design (SD) and residential mobility of students with disabilities (SWD) in off-campus student hostels in Ghana.

Quantitative research techniques were adopted. A sample of 243 SWD living in 190 University Student Housing were selected. Based on the SD indicators, the partial least square structural equation model was used to explore its effects on residential mobility in SWD living in university housing.

Findings indicate that a sense of control and positive distraction significantly influence residential mobility to a greater extent than social support design. While the sense of control emerged as a primary predictor of residential mobility, no direct relationships were observed between the sense of control, positive distraction and social support. Although social support did not exhibit significant direct effects, its potential relevance to residential mobility cannot be dismissed.

The enhancement and compliance of a sense of control and positive distraction SD in the common areas in student housing will reduce SWD residential mobility and increase investors’ profitability. Positive social support designs are critical to predicting percentage change in residential mobility in off-campus student housing in Ghana.

SD is a theory largely used in health-care buildings. The observation of no relationship between a sense of control and positive distraction, and social support aspects of SD in university housing in this study significantly differs from the inverse relationship that exists between SD in hospitals, especially in the developing world, is a theoretical contribution.

The significance of business processes has fostered a close collaboration between academia and industry. Moreover, the business landscape has witnessed continuous transformation, closely intertwined with technological advancements. Our main goal is to offer researchers and process analysts insights into the latest developments concerning artificial intelligence (AI) and machine learning (ML) to optimize their processes in an organization and identify research gaps and future directions in the field.

In this study, we perform a systematic review of academic literature to investigate the integration of AI/ML in business process management (BPM). We categorize the literature according to the BPM life-cycle and employ bibliometric and objective-oriented methodology to analyze related papers.

In business process management and process map, AI/ML has made significant improvements using operational data on process metrics. These developments involve two distinct stages: (1) process enhancement, which emphasizes analyzing process information and adding descriptions to process models and (2) process improvement, which focuses on redesigning processes based on insights derived from analysis.

While this review paper serves to provide an overview of different approaches for addressing process-related challenges, it does not delve deeply into the intricacies of fine-grained technical details of each method. This work focuses on recent papers conducted between 2010 and 2024.

This work addresses a significant gap by employing a pioneering approach to introduce challenges in BPM alongside AI/ML techniques and integrated tools. Hence, it offers comprehensive guidelines that elucidate the alignment between ML methods and solutions to current challenges across the BPM life-cycle, including process enhancement and process improvement. Additionally, by detailing various aspects of the life-cycle phases and highlighting ML technique characteristics, this research demonstrates potential approaches for future exploration, thereby enhancing applicability for both process analysts and researchers in this context.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).

The aim of the article was to compare the learning outcomes of the same content in the form of a traditional analogue lesson and in the form of a virtual reality (VR) lesson with the use of head-mounted display (HMD).

The study included one biology lesson conducted in 4 groups of a dozen people and one biology lesson in VR carried out individually on 75 people. The respondents completed the knowledge test, a questionnaire before and after the class regarding the attitude to new technologies, and feelings after the lesson. The researchers used detailed observation sheets (subjects' behaviour and the dynamics of the lesson). The obtained results were analysed statistically through lesson type (traditional/VR), respondent type (technology enthusiast/non-enthusiast) and question type. The Mann–Whitney U test, t-student and chi-squared (?²) test were used.

The average of the overall results in the knowledge test was similar in both groups (16 points; ±SD 2.13), slightly better for the analogue group and for the non-enthusiast group. It was found that VR hinders the acquisition of knowledge by tech enthusiasts, who perceive it primarily in the play paradigm. However, it encourages the learning of technology sceptics, who quickly discover a passion for exploring the virtual world. It was clearly indicated, quantitatively and qualitatively, how the technology modalities directly influenced the learning outcomes.

The article offers fresh insights into how students' perceptions of the educational process can be transformed through the integration of VR. The compelling findings and nuanced analysis provide a robust foundation for exploring new frontiers in educational technology.

Organisational slack has been widely considered in strategic management, but there is a gap in understanding the process of accumulation and application of slack resources. From a dynamic perspective and over an extended period of time, this paper analyses the management of slack resources and evaluates whether the different behaviours, in relation to the accumulation and consumption of slack resources, have any effect on performance.

The resource-based view and the dynamic extension of this theory, i.e. resource management and resource orchestration, were analysed in order to evaluate how slack resources can be managed and generate value. Assuming a configurational approach, the analysis was structured into two stages to answer the proposed hypothesis. The first stage studied whether there were different patterns of management of slack resources over time using the DistatisR package. The second stage evaluated which behaviours had the greatest impact in terms of profitability by using a dynamic panel data regression.

Three different types of slack resource management were found in companies: efficient, effective and erratic. Different types do not have the same impact on performance.

The dynamic management of slack resources has scarcely been considered, even during periods of crisis and economic expansion. This research advances the understanding of how firms transform slack resources into performance from a dynamic perspective.

Vertical urban settlements are becoming the predominant form of contemporary urban design in response to population increase and rapid urbanization. These developments are, however, perceived to be poorly designed and incongruent with the users’ needs. The purpose of this study was to present a resident satisfaction assessment of Hong Kong’s vertical settlements.

A review of the literature was conducted on the concept of vertical urbanism, residential satisfaction and postoccupancy evaluation. Fifty performance indicators were classified into three groups including indoor environment, safety and maintenance; furniture, utilities and spaces; and privacy, appearance and city life. These indicators were used to develop a Web-based questionnaire administered to residents in the three administrative regions of Hong Kong. Ninety-eight respondents participated in the study, and the results were analyzed using the resident satisfaction index and the overall satisfaction index. A multilinear regression analysis was also made to develop a model describing the most relevant performance indicators for determining the overall residential satisfaction.

The results revealed that residents expressed dissatisfaction with performance indicators, including “level of noise generated from outside the building (neighboring buildings, traffic, noise, etc.),” “variation and stability of indoor temperature,” “sustainable design of the building’s environment (cyclability, walkability, electric charging stations, etc.),” “availability and capacity of car parking,” “size and adequacy of spaces for social interaction” and “considerations for occupants with special needs (disabled, aged people, children, occupants with a medical condition, etc.).” The results also revealed that some indicators such as the maintenance of elevators, adequate interior space and surrounding areas were considered as significantly influencing residential satisfaction. Similarly, the building height and wind-induced motion were not significantly influencing residential satisfaction. The results also revealed that a multilinear Regression model with five variables and an adjusted R² value of 93% could estimate the overall residential satisfaction.

The concept of vertical urban design is the new paradigm in the shaping of future cities. The originality of this study is its adoption of post-occupancy evaluation to assess occupants’ residential satisfaction. As well as the determination of factors that should inform the planning, design and management of vertical urban settlements. Thus, the study has significant implications for research in vertical urban development, as well as the professional practice of building and urban planners, designers and managers.

Stock markets are considered as the largest and most important units for the development and growth of the economy. The present study attempts to provide a comprehensive view of factors influencing investment decision making process of stock market investors. A multi group analysis of gender is also carried out on the proposed model.

The data of 402 valid responses are collected through structured questionnaires from individual investors of North India. SPSS 23 is used to do the descriptive analysis and AMOS 22 is used to establish the validity of the constructs and for hypotheses testing. For performing multi group analysis, several invariance tests have also been conducted to check the robustness of the model.

The results reveal that all the factors such as firm image, accounting information, neutral information, advocate recommendation and personal financial needs significantly influence investment decision making concluding image of the firm being the most influential factor and advocate recommendation being the least influential factor for investment decisions. No significant differences between males and females were found.

The current study suffers from the limitation of restricted geographical area of North India. Moreover, there is also a scope to incorporate more demographic factors for predicting investment decisions.

This study incorporates a range of factors which covers all the aspects of investment decision making. This study also highlights the notion of signaling theory, thus contributing to the limited literature in Indian context.