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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.

Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

Trust is an important facilitator of successful B2B relationships. The purpose of this study is to investigate affect-based antecedents of both interpersonal and interorganizational trust, and their impact on the performance of buyer–supplier relationships. The authors ask two research questions: (1) What are affect-based dimensions of interpersonal and interorganizational trust? (2) How do interpersonal and interorganizational trust influence buyers’ operational performance?

The authors use data from an original survey of 156 buyer–supplier relationships between multinational enterprise subsidiaries and local suppliers in the Thai manufacturing sector to develop a structural model in which the authors test the hypotheses.

Consistent with social exchange theory and social psychology, the empirical analysis shows that affect-based dimensions at the individual level, namely, likeability, similarity and frequent social contact, and at the organizational level, namely, supplier firm willingness to customize and institutionalization of cooperation, are important for establishing trust. In addition, interpersonal trust enhances buyers’ operational performance indirectly via interorganizational trust.

Buying and selling firms may develop organizational trust by developing processes that enhance organizational trust. Individuals with purchasing or sales responsibilities may enhance trust in their personal relationship. However, such interpersonal trust needs to be translated to the organizational level to benefit organizational performance.

The findings contribute to the literature on affect-based antecedents and outcomes of trust. Specifically, the authors offer theory and empirical evidence regarding the contribution of salespersons toward affect-based dimensions of trust and its impact on buyer’s operational performance.

This study aims to assess the risk profile of millennial investors residing in the Delhi NCR region. In addition, the relationship between the risk profile and demographic traits of millennial investors was also analyzed.

Data was collected using a structured questionnaire segregated into two sections. In the first section, millennials were asked questions on socio-demographic factors, and the second section contained ten Likert-type statements to cover the multidimensionality of financial risk. Factor analysis and one-way ANOVA were used to analyze the primary data collected for this study.

The findings indicate that the risk profile of millennials is mainly affected by three factors: risk-taking capacity, risk attitude and risk propensity. Except for educational qualification and occupation, all other demographic features, such as age, gender, marital status, income and family size, seem to significantly influence the factors defining millennials' risk profile.

Uncertainty is inherent in any financial decision, and an investor’s willingness to deal with these variations determines their investment risk profile. To make sound financial decisions, it is mandatory to understand one’s risk profile. The awareness of millennials' distinctive risk profile will come in handy to financial stakeholders because they account for one-third of India’s population, and their financial decisions will shape the financial world for the decades to come.

Based on the theoretical framework, this paper analyzes the sentiment-herding relationship in emerging stock markets (ESMs). First, it aims to examine the effect of investor sentiment on herding. Second, it seeks the direction of causality between sentiment and herding time series.

The present study applies the Exponential Generalized Auto_Regressive Conditional Heteroskedasticity (EGARCH) model to capture the volatility clustering of herding on the financial market and to investigate the role of the investor sentiment on herding behaviour. Then the vector autoregression (VAR) estimation uses the Granger causality test to determine the direction of causality between the investor sentiment and herding. This study uses a sample consisting of stocks listed on the Shanghai Composite index (SSE) (348 stocks), the Jakarta composite index (JKSE) (118 stocks), the Mexico IPC index (14 stocks), the Russian Trading System index (RTS) (12 stocks), the Warsaw stock exchange General index (WGI) (106 stocks) and the FTSE/JSE Africa all-share index (76 stocks). The sample includes 5,020 daily observations from February 1, 2002, to March 31, 2021.

The research findings show that the sentiment has a significant negative impact on the herding behaviour pointing out that the higher the investor sentiment, the lower the herding. However, the results of the present study indicate that a higher investor sentiment conducts a higher herding behaviour during market downturns. Then the outcomes suggest that during the crisis period, the direction is one-way, from the investor sentiment to the herding behaviour.

The findings may have implications for universal policies of financial regulators in EMs. We have found evidence that the Emerging investor sentiment contributes to the investor herding behaviour. Therefore, the irrational investor herding behaviour can increase the stock market volatility, and in extreme cases, it may lead to bubbles and crashes. Market regulators could implement mechanisms that can supervise the investor sentiment and predict the investor herding behaviour, so they make policies helping stabilise stock markets.

The originality of this paper lies in investigate the sentiment-herding relationship during the Surprime crisis and the Covid-19 epidemic in the EMs.

This study aims to examine the performance implications of an information governance (IG) framework for managing, controlling access to and securing information, focusing on (1) the performance benefits of an organization's IG orientation and (2) how the configuration of IG orientation and supply chain (SC) strategy type relate to performance outcomes.

This study leverages multiple secondary sources for US hospitals, serving as the context for the study. It also employs cluster analysis to develop an SC strategy taxonomy, namely sophisticated and delivery-focused SC strategies. The proposed research model is tested using a robust regression to mitigate the influence of outliers and produce more accurate estimates.

IG orientation is positively associated with financial performance and patient experience, and IG-oriented hospitals with a sophisticated SC strategy realize more financial benefits and achieve better patient care experiences compared to other configurations. Regardless of SC strategy type, IG-oriented hospitals offer better care experiences than non-IG-oriented hospitals.

This paper offers empirical evidence that a hospital's IG orientation and SC strategy jointly affect financial outcomes and patient experience. For hospitals, an organization-wide framework for governing information streamlines both intra- and inter-organizational information flows and improves care delivery throughout a patient's care experience.

This is one of a few studies that empirically examine the performance implications of governance of information in the domain of supply chain management (SCM). This study also develops an SC strategy taxonomy for the healthcare context and offers a springboard for research in service SC strategy.

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.

A sense of collective free-thinking with tangible goals makes co-creation an enlightening experience. Yet despite the freedom and organic flow of the methodology, there remain barriers to deploying co-creation in the real-world context. The aim was to understand the barriers and solutions to co-creation, reflect on applying co-creation in practice and co-create an applicable framework for co-creation.

These reflections and conceptual developments were completed using a Participatory Action Research Approach through the co-creation of the Erasmus+ funded Co-creating Welfare course.

Results presented are centric to the experiences in the United Kingdom but led to application at an international level. Problem formulation led to solutions devised about who should co-create, what co-creation aims to achieve, how to receive management buy-in, co-creating beyond the local face to face context and evaluation.

The Three Co’s Framework is proposed using the outline of: Co-Define, Co-Design and Co-Refine. Those who take part in co-creation processes are recommended to be called co-creators, with less focus on “empowerment” and more about facilitating people to harness the power they already have. Utilising online and hybrid delivery methods can be more inclusive, especially in response to the COVID-19 pandemic. The use of co-creation needs to be evaluated more moving forwards, as well as the output co-created.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

Forced labour is one of the most exploitative practices in supply chains, generating serious human right abuses. The authors seek to understand how relationships for reducing forced labour are influenced by institutional logics. The emerging supply chain efforts of social enterprises offer particularly intriguing approaches, as their social mission can spur creative new approaches and reshape widely adopted management practices.

The authors study supplier relationships in the smartphone industry and compare the evolving practices of two cases: the first, a growing novel social enterprise; and the second, a high-profile commercial firm that has adopted a progressive role in combating forced labour.

The underlying institutional logic influenced each firm's willingness to act beyond its direct suppliers and to collaborate in flexible ways that create systematic change. Moreover, while both focal firms had clear, well-documented procedures related to forced labour, the integration, rather than decoupling, of forced labour and general supply chain policies provided a more effective way to reduce the risks of forced labour in social enterprises.

As authors’ comparative case study approach may lack generalizability, future research is needed to broadly test their propositions.

The paper identifies preconditions in terms of institutional logics to successfully reduce the risk of forced labour in supply chains.

This paper discusses how social enterprises can provide a learning laboratory that enables commercial firms to identify options for supplier relationship improvement.