Search results

This study introduces a non-orthodox approach to the dominant policy-based approaches to graduate employability through contextualizing international students’ everyday experiences within their educational and wider structural contexts of the labour market.

The study used narrative frames to collect data from 180 international students from China, Hong Kong, India, Sri Lanka, Vietnam and Nepal at a New Zealand tertiary institution. Narrative frames as a research tool in educational contexts are used to ellicit the experiences of individuals in the form of a story as participants reflect on their experience. The frames use sentence starters to draw responses from participants about their experiences (Barkhuizen and Wette, 2008).

This study argues that, through a socialization process, international students develop identities that fit an ever-changing labour market. This process is catalysed by a higher education landscape that produces career-ready subjects capable of appropriating different social spaces that prepare students and graduates to enter the labour market. Further, it argues that graduate employability should be understood as a complex process through which students and graduates socialise themselves through negotiating the socioacademic spaces by (1) familiarising themselves with the dominant workspace norms, (2) positioning themselves as more career-ready individuals, and (3) imagigining employable selves capable of meeting the needs of the job market.

This study has limitations. Only one data collection source has been used. It would have been great to use narrative frames along with interviews. In addition, the data would have been stronger if the researcher could have used classroom observations, which could be a future initiative.

This study could provide practical insights to tertiary institutions about international students’ developing capabilities and identities so they could better prepare themselves for the world of work. Further, this study provides insights about some of the challenges that international students face in tertiary contexts to become career-ready. Hence, educators could employ strategies to better support these learners in their everyday learning spaces. This study also has useful benefits for future and current international students and international graduates regarding what investments they need to make so they can better socialize themselves in their tertiary and workplace practices.

This study has social implications. It helps international students better understand the social, cultural and academic expectations of their host countries. Therefore, they could better socialize themselves into those practices and contribute more effectively to their academic and workplace communities. The study also helps academic and workplace institutions strategize more effectively to address the social and cultural needs of international graduates. The study also contributes to the social and cultural understanding of the teachers that engage with international students on a daily basis by helping them devise activities that better address these students’ and graduates’ needs.

The study adds theoretical and methodological value to the debates around graduate employability. It includes the voices of 180 students and unravels their day-to-day experiences of capability building and employability development from their own perspectives.

Drawing on a theoretical framework of sustainable career ecosystem theory, our paper aims to consider how domestic and international postgraduates can enhance their employability through participation in a landscape of practice.

The study employed an exploratory, longitudinal case study design to capture students' lived experiences on an 18-month Master of Professional Practice course at a higher education institution in New Zealand. The data collection procedure involved field note observations (months 1–4), a focus group (month 13) and narrative frames (months 16–18). The sample was domestic students from New Zealand (n = 2) and international students from Asia (n = 5).

One’s participation in multiple communities of practice represents their landscape of practice and a commitment to lifewide learning. Through participation in various communities of practice, domestic and international students can enhance their employability in three ways: (1) boundary encounters to develop social capital, (2) transcending contexts to enhance cultural capital, and (3) acknowledging the development of psychological capital and career agency.

Our work offers one of the earliest empirical validations of sustainable career ecosystem theory. Expressly, communities of practice represent various contexts whereby employability capital is developed over time. Additionally, the postgraduate students themselves are portrayed as interconnected and interdependent actors, presenting a novel framing of such dependencies at the micro-level of the ecosystem. The practical implications come from informing universities of the value of a landscape of practice to enhance the employability of domestic and international students in preparation for sustainable careers and to promote the sustainability of the career ecosystem.

This paper aims to investigate an integrated approach that aims at enhancing the application process of value stream mapping (VSM) method. It also proposes an extended VSM called Economic and Environmental VSM(E-EVSM). The proposed approach highlights the improvement of economic and environmental performances.

The proposed approach has studied the integration of VSM, fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy quality function deployment (QFD) to improve the economic and environmental performances of manufacturing processes. The VSM method is used for data collection and manufacturing process assessment, whereas fuzzy DEMATEL is used to analyse the current state map. Finally, fuzzy QFD is used to organize the improvement phase of VSM method.

The clear findings of this research prove the effectiveness of VSM method on the environmental and economic performances of manufacturing processes. In addition, the proposed approach will show the advantages of fuzzy DEMATEL and fuzzy QFD approaches in improving the application of the VSM method.

The limitation of this study includes the lack of consideration of other dimensions such as social, technological and managerial. In addition, the proposed approach studied an average set of environmental and economic indicators.

The novelty of the proposed approach is proved by the development of an extended VSM method (E-EVSM). Also, the proposed approach contributes by a new methodology for analysing and improving the current state map of manufacturing processes.

The purpose of this study is truck scheduling and assignment of trucks to the doors simultaneously since these issues were considered mainly separately in the previous research. Also, the door service time and its impact on truck scheduling were not taken into account, so this research endeavors to cover this gap.

In this research, a novel model has been presented for simultaneous truck scheduling and assignment problem with time window constraints for the arrival and departure of trucks, mixed service mode dock doors and truck queuing. To resolve the developed model, two meta-heuristic algorithms, namely, genetic and imperialist competitive algorithms, are presented.

The computational results indicate that the proposed framework leads to increased total costs, although it has a more accurate planning; moreover, these indicate that the proposed algorithms have different performances based on the criteria considered for the comparison.

There are some limitations in this research, which can be considered by other researchers to expand the current study, among them the specifications of uncertainty about arrival times of inbound and outbound trucks, number of merchandises which has been loaded on inbound trucks are the main factors. If so, by considering this situation, a realistic scheme about planning of cross docking system would be acquired. Moreover, the capacity of temporary storage has been considered unlimited, so relaxing this limitation can prepare a real and suitable situation for further study. Examining the capacity in the front of each type of doors of cross-dock and executive servers are the other aspects, which could be expanded in the future.

In this study, a mathematical programing model proposed for truck scheduling to minimize total costs including holding, truck tardiness and waiting time for queue of trucks caused by the interference of each carrier’s movement. At the operational levels, this research considered a multi-door cross-docking problem with mixed service mode dock doors and time window constraints for arrival and departure time of trucks. Moreover, M/G/C queue system was developed for truck arrival and servicing of carriers to trucks.

This study aims to examine the potential of two artificial intelligence (AI)-based algorithms, namely, adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP), for indirect estimation of the ultimate bearing capacity (q_ult) of rock foundations, which is a considerable civil and geotechnical engineering problem.

The input-processing-output procedures taking place in ANFIS and GEP are represented for developing predictive models. The great importance of simultaneously considering both qualitative and quantitative parameters for indirect estimation of q_ult is taken into account and explained. This issue can be considered as a remarkable merit of using AI-based approaches. Furthermore, the evaluation procedure of various models from both engineering and accuracy viewpoints is also demonstrated in this study.

A new and explicit formula generated by GEP is proposed for the estimation of the q_ult of rock foundations, which can be used for further engineering aims. It is also presented that although the ANFIS approach can predict the output with a high degree of accuracy, the obtained model might be a black-box. The results of model performance analyses confirm that ANFIS and GEP can be used as alternative and useful approaches over previous methods for modeling and prediction problems.

The superiorities and weaknesses of GEP and ANFIS techniques for the numerical analysis of engineering problems are expressed and the performance of their obtained models is compared to those provided by other approaches in the literature. The findings of this research provide the researchers with a better insight to using AI techniques for resolving complicated problems.

When a large-scale outbreak such as the COVID-19 pandemic happens, organizations that are responsible for delivering relief may face a lack of both provisions and human resources. Governments are the primary source for the humanitarian supplies required during such a crisis; however, coordination with humanitarian NGOs in handling such pandemics is a vital form of public-private partnership (PPP). Aid organizations have to consider not only the total degree of demand satisfaction in such cases but also the obligation that relief goods such as medicine and foods should be distributed as equitably as possible within the affected areas (AAs).

Given the challenges of acquiring real data associated with procuring relief items during the COVID-19 outbreak, a comprehensive simulation-based plan is used to generate 243 small, medium and large-sized problems with uncertain demand, and these problems are solved to optimality using GAMS. Finally, post-optimality analyses are conducted, and some useful managerial insights are presented.

The results imply that given a reasonable measure of deprivation costs, it can be important for managers to focus less on the logistical costs of delivering resources and more on the value associated with quickly and effectively reducing the overall suffering of the affected individuals. It is also important for managers to recognize that even though deprivation costs and transportation costs are both increasing as the time horizon increases, the actual growth rate of the deprivation costs decreases over time.

In this paper, a novel mathematical model is presented to minimize the total costs of delivering humanitarian aid for pandemic relief. With a focus on sustainability of operations, the model incorporates total transportation and delivery costs, the cost of utilizing the transportation fleet (transportation mode cost), and equity and deprivation costs. Taking social costs such as deprivation and equity costs into account, in addition to other important classic cost terms, enables managers to organize the best possible response when such outbreaks happen.

This paper examines the socio-ecological co-evolution and transformation of organic pioneers and the organic food market from a politically structuring actor perspective. It aims to identify strategies and activities used to contribute to the change of structures in the organic market and how the companies, in turn, reacted to the structural influence of the changing environment to position their company successfully in the market.

This study is based on interviews with four managing directors who were responsible over several decades for the strategic corporate management of the pioneer companies they founded as (or converted to) organic. Content analysis was used to analyse the data.

Strategic challenges regarding building up, maintaining and using resources, shaping actor constellations, and professionalising management are explained. The analysis demonstrates that also small pioneers have the possibilities and scope to influence and change markets and structures.

The results are significant for developing sustainable transformation strategies for markets, considering the interaction of the micro and meso-levels over time and the role of small businesses that might be struggling with growth and loss of values. The study answers recent calls in the literature to empirically investigate sustainability transformations from a practice perspective and gain insights into the roles of corporate actors.

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.