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Despite increased interest in the Operator 4.0 concept, there has been scarce attention on practice-oriented frameworks that can assist firms in reaping the potential benefits of technologies within the I4.0 framework. The purpose of this paper is to provide an integrative framework on how to engage Operator 4.0 effectively.

Following meta-synthesis logic and integrative conceptual analysis, this study synthesizes and integrates experimental case studies on Operator 4.0 solutions. The analysis is conducted on 24 cases retrieved from peer-reviewed articles.

The analysis revealed several factors that determine the type and extent of benefits that can be realized within a human-cyber-physical system. However, enhancing these capabilities is not straightforward, as several factors can inhibit the realization of these capabilities. Firstly, the benefits vary depending on the type of Operator 4.0. Secondly, the interoperability of the introduced I4.0 solution with the existing systems is crucial. Thirdly, the adaptability of the solution to serve multiple purposes is crucial, as it tends to increase technology acceptance.

The studies reviewed in this research were based on experimental cases, with limited implementation of the solutions they proposed. As such, their implications when implemented on a larger scale are tentative.

The present study has synthesized existing experimental cases and developed an integrative framework to guide the implementation of Operator 4.0. By gathering primary insights from these experiments, we have clarified when and how Operator 4.0 and the required interactions can lead to successful implementation.

We examined skill building techniques and changes over the course of a semester with pre and post-test data collection after implementing experiential learning assignments.

The Schutte Self-Report Emotional Intelligence Test (SEEIT) was used to measure emotional intelligence among students who interned for a 16-week period.

We found a significant difference using a paired samples t-test in SSEIT scores between the pre (M = 126.6, SD = 4.3) and the post-internship (M = 133.8, SD = 5.7) scores. t(5) = -5.61, p = 0.002. Students had an overall increase in mean scores over the course of one semester.

This was a pilot study that we completed to determine applicability of internship and increasing emotional intelligence. Overall, we saw an increase in EI in pre and post-test comparisons. This was a pilot study, so more research is needed on this topic.

Students were placed in situations during the internship process to help facilitate real world problems and were required to apply applicable textbook knowledge, develop theory-based activities and report their findings. Students worked with various age groups and learned how to work with a variety of populations including faculty, teachers, children and parents on a regular basis and this process contributed to their experience and potentially increased emotional intelligence over a 16-week period.

This research addresses the importance of emotional intelligence (EI) in career readiness and its role in potentially mitigating burnout in psychological professions.

This is important to those in the field of psychology and child development and family studies because it addresses concerns with the shortage of skilled and prepared workers.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

A better understanding of the characteristics and capabilities of women entrepreneurs can significantly improve their chances of success. Therefore, three studies were conducted for this exploratory paper. We have discovered the characteristics of entrepreneurial intelligence among female entrepreneurs through semi-structured interviews based on conventional content analysis. According to the second study, qualitative meta-synthesis was utilized to identify characteristics of women's entrepreneurial intelligence at the international level. As a third study, we examined the evolutionary relationships of entrepreneurs' intelligence components following the discovery and creation of opportunities.

The present paper was based on three studies. In the first study, 15 female entrepreneurs were interviewed using purposive sampling in the Guilan province of Iran to identify the characteristics of entrepreneurial intelligence at the national level. An inductive content analysis was performed on the data collected through interviews. Using Shannon entropy and qualitative validation, their validity was assessed. In the second study, using a qualitative meta-synthesis, the characteristics of women's entrepreneurial intelligence were identified. Then the results of these two studies were compared with each other. In the third study, according to the results obtained from the first and second studies, the emergence, priority and evolution of entrepreneurial intelligence components in two approaches to discovering and creating entrepreneurial opportunities were determined. For this purpose, interviews were conducted with 12 selected experts using the purposeful sampling method using the fuzzy total interpretive structural modeling (TISM) method.

In the first research, this article identified the components of entrepreneurial intelligence of women entrepreneurs in six categories: entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. In the second study, the components of entrepreneurial intelligence were compared according to the study at the national level and international literature. Finally, in the third study, the evolution of the components of entrepreneurial intelligence was determined. In the first level, social intelligence, presumptuous intelligence and provocative intelligence are formed first and social intelligence and provocative intelligence have an interactive relationship. In the second level, entrepreneurial insight and cognitive intelligence appear, which, in addition to their interactive relationship, take precedence over the entrepreneur's intuitive intelligence in discovering entrepreneurial opportunities. With the evolution of the components of entrepreneurial intelligence in the opportunity creation approach, it is clear that intuitive intelligence is formed first at the first level and takes precedence. At the second level, there is cognitive intelligence is created. At the third level, motivational intelligence and finally, at the last level, entrepreneurial insight, social intelligence and bold intelligence.

This study has the potential to discover credible and robust approaches for further examining the contextualization of women's entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various components of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women's entrepreneurship, this paper challenges the assumption that the characteristics of women's entrepreneurial intelligence are uniform worldwide. It also depicts the evolution of the components of entrepreneurial intelligence.

A key challenge for exporters and international marketing/purchasing managers is formulating strategic responses to deal with geopolitical disruptions during a trade war between superpowers. While past studies provide insightful analysis of the influence of changes in the institutional environment (regulatory pressures) on national and firm-level trade activities, they tend to ignore the association between inward (sourcing) or outward (export) international activities of firms during a trade war. In this study, we aim to explore various strategic options employed by third-party SME exporters in response to geopolitical disruptions, institutional pressures and constraints during a trade war.

We adopted a qualitative methodology and applied a hermeneutical approach in collecting, analysing and theorising interview findings. We conducted interviews with 15 owners or senior managers from 12 Australian and New Zealand exporters that exported or sourced significantly from at least one party of the trade war, the USA or China, between 2018 and 2020.

Our study developed a typology of fencing vs. balancing for explaining third-party SME exporters’ response strategies in terms of export market and international sourcing locations during a trade war. Fencing strategy centres on location choice decisions based on a fence or a secure buffer zone. Balancing strategy focuses on leveraging opportunities outside the conflict zone, i.e. third-party countries. Our study finds that exporters’ location choice decisions are influenced by a number of institutional factors during the trade war.

Firstly, our study examined only the early phase of the trade war under the “Trump” era. Future research may consider a longitudinal study design that examines exporters’ responses to global political uncertainty over a longer term. Secondly, we chose Australia and New Zealand as the focal context of this study. Future research could investigate exporters from other third-party countries that have different institutional conditions during the US-China trade war.

Firstly, an exporting firm should monitor and assess closely the wider changes in international relations between their home country’s major security partner and major trading partner, and the impact of these changes on the political risks of operating in international locations. Secondly, as the trade war intensifies, the fencing option needs to be given a greater weight than the balancing option in the strategic decision making of an exporter from a third-party country. Lastly, we encourage marketers and managers to reflect on and differentiate short-term and long-term benefits in strategic market-sourcing location decisions.

Our study makes a pioneering effort to theorise the linkages between institutional factors and the combined evaluation of export market selection and sourcing location selection choices under global political uncertainty based on the institution-based view. We present a conceptual framework highlighting the importance of institutional avoidance, embeddedness, comparative institutional advantages and multiple institutional logics for SME exporters’ international location selections during the trade war. Furthermore, we combine these institutional factors into two overarching constructs namely institutional buffer and institutional pluralism.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

The paper proposes a privacy-preserving artificial intelligence-enabled video surveillance technology to monitor social distancing in public spaces.

The paper proposes a new Responsible Artificial Intelligence Implementation Framework to guide the proposed solution's design and development. It defines responsible artificial intelligence criteria that the solution needs to meet and provides checklists to enforce the criteria throughout the process. To preserve data privacy, the proposed system incorporates a federated learning approach to allow computation performed on edge devices to limit sensitive and identifiable data movement and eliminate the dependency of cloud computing at a central server.

The proposed system is evaluated through a case study of monitoring social distancing at an airport. The results discuss how the system can fully address the case study's requirements in terms of its reliability, its usefulness when deployed to the airport's cameras, and its compliance with responsible artificial intelligence.

The paper makes three contributions. First, it proposes a real-time social distancing breach detection system on edge that extends from a combination of cutting-edge people detection and tracking algorithms to achieve robust performance. Second, it proposes a design approach to develop responsible artificial intelligence in video surveillance contexts. Third, it presents results and discussion from a comprehensive evaluation in the context of a case study at an airport to demonstrate the proposed system's robust performance and practical usefulness.

The purposes of this paper are to examine the factors persuasive in building competitive advantage strategies for the co-living and co-working service operators and study the sustainability of the business model for co-living and co-working space.

In this research, a structured literature review of journals, articles, reports, conference proceedings, websites published in recent times and e-newspapers has been conducted. The first step of the research included identifying the relevant literature. For this step, multiple keywords were used in searching for literature on Google.com, Google Scholar, Proquest, Taylor & Francis, Emerald, Elsevier. Upon literature identification, the procured reports were divided into the following three parts: co-living reports, co-working report and others. More than 250 content reports were analyzed, and finally, 105 relevant literature reports from various sources were recorded for further analysis. Focus group discussion and semi-structured interviews were also conducted.

This study concluded after analyzing the literature, focus group discussion and semi-structured interviews that co-working and co-living space would be sustainable business if proper competitive strategies were leveraged, in accordance with the increase in demand over time. This study also serves as a wakeup call for the operators in the co-living and co-working sphere to work on their competitive advantages and differentiate themselves to tap business opportunities. The sustainability of the model by identifying the factors was also emphasized in this study. Further studies of co-living and co-working models should be conducted in the Indian context to analyze the multifarious potential that this new trend of shared accommodation can open up.

This study is based on content analysis, focus group discussion and semi-structured interview analysis. More content and literature were found to be evidenced mostly in Western literature. This is a limitation to the study. This study also had a limitation in including bigger sample of focus groups discussion and interviews; however, the analysis effectively set out a landscape of co-living and co-working space in India.

It is an original research work based on an existing concept and services. As co-living and co-working service operators are cropping up in major cities, enticing the target potential with a platter of services primarily linked with many of the beneficial factors, the researchers in this work attempt to examine the factors persuasive in building the competitive advantage strategies for the co-living and co-working space and the sustainability of these two business models. A ripe market with multifarious possibilities waiting to be tapped with the right plan of action is the need of the hour.

Nursing students encounter a combination of academic rigor, clinical demands and emotional hurdles. Juggling coursework, practical training and patient interaction can be stressful, and exposure to such situations may impact their psychological well-being. This study aims to highlight the top strengths among nursing students and identify the strengths associated with well-being.

Convenience sampling was used to select a sample of 150 nursing students studying in first, second and third year from colleges of Gujarat and Rajasthan. Students were administered the Values In Action character strengths inventory, the satisfaction with life scale and scale of positive and negative experience. Data was analyzed using descriptive statistics and correlation.

Results show that among nursing students, kindness emerged as the foremost strength with the highest mean, followed by honesty, creativity, spirituality and teamwork, and the strengths of curiosity, gratitude, perseverance, self-regulation, social intelligence, and zest were positively associated with life satisfaction and positive emotions and negatively related to negative emotions.

The small sample size was a limitation; however, this study has been conducted at different locations to improve generalizability.

This study has profound implications for nursing students, both in their personal development and their future roles as health-care professionals, as fostering these attributes can contribute to the students’ growth, well-being and effectiveness as compassionate and competent caregivers. Working on strengths is associated with well-being; therefore, using strengths identified by this study will have a beneficial effect on the students’ well-being.

Curiosity and social intelligence, for instance, can help nurses better understand patient needs and emotions, developing strengths like perseverance and self-regulation can equip nursing students with tools to cope effectively with the challenges inherent in health-care settings. Traits such as gratitude and social intelligence can enhance communication and empathy which are vital skills for establishing rapport with patients and their families. Emphasizing teamwork as a strength aligns with the collaborative nature of health care. By embodying values like kindness and spirituality, nursing students can create a more compassionate and meaningful experience for patients, as well as themselves.

The research paper identifies and emphasizes the five character strengths that are most commonly observed in a sample of Indian nursing students. In addition, this study delves deeper into these identified strengths to understand how they relate to the overall well-being of nursing students within this specific population. The existing literature has not explored it exhaustively.