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Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

Untimely responses to emergency situations in urban areas contribute to a rising mortality rate and impact society's primary capital. The efficient dispatch and relocation of ambulances pose operational and momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given to the optimal allocation of technicians to respond to emergency situation and minimize overall system costs.

In this paper, a bi-objective mathematical model is proposed to maximize system coverage and enable flexible movement across bases for location, dispatch and relocation of ambulances. Ambulances relocation involves two key decisions: (1) allocating ambulances to bases after completing services and (2) deciding to change the current ambulance location among existing bases to potentially improve response times to future emergencies. The model also considers the varying capabilities of technicians for proper allocation in emergency situations.

The Augmented Epsilon-Constrained (AEC) method is employed to solve the proposed model for small-sized problem. Due to the NP-Hardness of the model, the NSGA-II and MOPSO metaheuristic algorithms are utilized to obtain efficient solutions for large-sized problems. The findings demonstrate the superiority of the MOPSO algorithm.

This study can be useful for emergency medical centers and healthcare companies in providing more effective responses to emergency situations by sending technicians and ambulances.

In this study, a two-objective mathematical model is developed for ambulance location and dispatch and solved by using the AEC method as well as the NSGA-II and MOPSO metaheuristic algorithms. The mathematical model encompasses three primary types of decision-making: (1) Allocating ambulances to bases after completing their service, (2) deciding to relocate the current ambulance among existing bases to potentially enhance response times to future emergencies and (3) considering the diverse abilities of technicians for accurate allocation to emergency situations.

In a conventional sense, information technology has frequently been considered a source of Lean waste management. However, as the corporate world evolves, new models that provide a competitive edge by merging technical breakthroughs with the Lean paradigm must be developed. Enterprise resource planning (ERP), which is such technological advancement, is found to be highly influential for Lean implementation. However, there is a dearth of literature on the adaptability of ERP to minimise Lean waste in the construction industry. This paper, therefore, aims to investigate the possibility of applying ERP to minimise Lean waste in the construction industry.

The study used a qualitative approach, consisting of fifteen (15) expert interviews and code-based content analysis was used to analyse the empirical data.

The findings revealed the challenges faced when applying ERP with the Lean concept and the strategies that would help overcome the challenges. Most of the challenges could be overcome through training and awareness programmes and proper team management. The study also found that ERP could be applied with Lean to eliminate waste generation in the construction industry.

This paper contributes to the theory by providing an evaluation of the possibility of adopting ERP to eliminate Lean waste in the construction industry. The study will contribute to new knowledge related to strategies for proper use of ERP for Lean waste minimisation, which will be useful for future researchers in the area.

Miscarriage is the most common adverse pregnancy outcome, with an estimated one in four pregnancies ending in loss. Despite its prevalence, and significant effects, early pregnancy loss is commonly unacknowledged by organizations, and the intersect of miscarriage experiences while navigating work remains sparsely researched. Available literature, and preliminary research from my Ph.D., reveal stark findings, notably that women commonly conceal miscarriage at work, and when they do disclose, they often experience inconsistent support, or none at all. Minimization, and even discriminatory practice, are commonly witnessed (including inappropriate absence reporting, formal warnings, jeopardization of promotional opportunities, and redundancy). Effective support is often due to empathetic line managers, who sometimes have first-hand experience. Partners are commonly assigned to the “supporter role”, resulting in insufficient leave and support. The absence of formal initiatives, including policy and training, exacerbate the issue. Workplaces that fail to address miscarriage likely face reduced engagement and productivity, and increased absenteeism, presenteeism, and staff turnover. Key recommendations are presented, emphasizing the need for organizations to (i) implement a pregnancy loss policy; (ii) train managers, HR, and colleagues; (iii) provide specialist support; and (iv) tackle pro-natal cultures. Avenues for future research are explored, notably the need to adopt an intersectional lens, and to obtain management/HR and partner perspectives.

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode.

This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool.

It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm³/min and 0.001034 g/min, respectively.

Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

This study aims to examine the relationships among senior managers’ reports of bribery practices, ethical awareness and firm productivity in Thailand. Bribery pervasiveness is examined as moderating the relationship between bribery practices and ethical awareness. Ethical awareness is examined as a mediating effect of bribery practices and managerial perceptions of firm productivity.

This study uses a mixed-method approach consisting of interviews with more than 20 senior managers and surveys collected from more than 200 senior managers in Thailand’s manufacturing and construction industries. Hierarchical regression is used to test the hypotheses.

Senior managers report that their firms are more likely to flout ethical principles when they perceive that their industries feature widespread bribery practices. However, the tests fail to support the hypothesis that the flouting of ethical principles leads to less productivity.

This study contributes to transaction cost economics theory by extending the concept of illegal transaction cost minimization to managerial perceptions of firm productivity. This study also integrates research on bribery rationalization by considering how managerial rationalization and justification of bribery practices impact managerial perceptions of firm productivity and ethical awareness. This research provides managers with an understanding of how attitudes toward ethical conduct and unethical actions impact perceptions of firm productivity.

This case study provides in-depth, practical knowledge to develop business strategies for the management program. After reading this case study, the students will be able to learn about the challenges and problems that service firms face during a crisis, the drastic changes in the market environment due to a crisis and the analysis tools that can be used when analyzing the shifted market environment. By analyzing this case study, students will be trained for the decision-making that arises in the process of crisis management in the hotel industry.

Nam Nghi Resort, situated on the picturesque Phu Quoc Island in Vietnam, experienced the tumultuous period of the COVID-19 pandemic. Before the pandemic, Nam Nghi was a thriving five-star resort, deeply rooted in Vietnamese culture and renowned for its luxurious amenities and breathtaking location. However, the onset of COVID-19 brought unprecedented challenges to the hospitality industry, leading to a sharp decline in tourism and revenue. Despite the adversity, Nam Nghi implemented risk management practices successfully and displayed resilience and adaptability. Through rigorous cost minimization, strategic facility upgrades and targeted marketing efforts, Nam Nghi managed to navigate the crisis and gradually rebuild its business as travel restrictions eased. As the industry began to show signs of recovery, the general manager faced new challenges in restoring the resort’s prepandemic vitality. The challenge remained of understanding changing consumer values and market dynamics.

This case study can be used as class material for Master of Business Administration (MBA) students. In particular, MBA students in the hospitality industry such as hotels, resorts, travel agencies and restaurants are the target audience.

Teaching notes are available for educators only.

CSS 12: Tourism and hospitality.

The UAE is among the fastest-growing facilities management (FM) markets globally. Nevertheless, conclusive evidence on this market is scarce in the literature. Therefore, this paper aims to provide an in-depth insight into the FM market in the UAE.

Fourteen interviewees were purposively selected to provide insight into FM status through their field experiences. A SWOT analysis of their answers held place.

Interviewees revealed that the main trends of FM in the UAE include interests in sustainability, integration of technology, health and safety, outsourcing FM, switching to total facilities management (TFM), and performance management systems use. Besides, the quality of the service in the FM market is driven by the real-estate boom, services sophistication, the increasing awareness of FM and focus on the quality of services. Furthermore, the interviews found that the recruitment of poorly skilled labors can threaten the FM market to meet the allocated budget, misperception of FM, the value of money, the lack of continuous follow-up with recent advancements in technologies and the lack of performance measurement models.

This paper highlights the major trends, drivers and threats of the FM market in the UAE, and the implications of its findings can direct FM organizations and researchers in their practices.

Social entrepreneurship (SE) is a complex phenomenon designed to resolve numerous societal challenges while remaining economically viable. However, how social entrepreneurs in developing countries have deployed digital technologies to address communal challenges during the Covid-19 crisis is largely undocumented. This research examines social entrepreneurs' adoption of digital technologies, the multi-level organisational conditions, and associated innovative outcomes of engaging digital technologies.

Based on the organisational resilience theoretical framework, this research employs a qualitative methodology, comprising 38 semi-structured interviews with Nigerian SE firms, to investigate social entrepreneurs' engagement with digital technologies.

The study’s findings reveal 19 pathways through which digital technologies enabled organisational resilience outcomes by Nigerian SE firms during the Covid-19 pandemic. This allows the authors to show, via a 3 × 3 matrix, how social entrepreneurs deploy digital technologies to build proximate, dynamic, and continuous resilience in a weak institutional context.

The study’s findings enables the authors to advance the SE – digital technologies – resilience scholarship in a developing economy.