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Over the past two decades, the hub location domain has witnessed remarkable growth, yet no prior study reviewed and synthesised problem formulation and solution methodologies to address real-life challenges.

The current study conducts a comprehensive bibliometric literature review to develop a thematic framework that describes and presents hub location problems. The work employs cluster, bibliometric, and social network analyses to delve into the essential themes.

Key themes include cooperation, coopetition, sustainability, reshoring, and dynamic demand, contributing to the complex challenges in today’s hub location problems. As the first work in this field, the study serves as a valuable single-source reference, providing scholars and industry practitioners with key insights into the evolution of hub location research, prominent research clusters, influential authors, leading countries, and crucial keywords.

Findings have significant implications since they highlight the current state of hub location research and set the stage for future endeavours. Specifically, by identifying prominent research clusters, scholars can explore promising directions to push the boundaries of knowledge in this area.

This work is a valuable resource for scholars in this domain and offers practical insights for industry practitioners seeking to understand the hub location problems. Overall, the study’s holistic approach provides a solid foundation for advancing future research work in the hub location field.

This study was conducted to analyze the effects of machining parameters on the specific energy consumption in the computerized numerical control lathe turning operation of a hardened alloy steel roll at low cutting speeds. The aim was to minimize its consumption.

The design matrix was based on three variable factors at three levels. Response surface methodology was used for the analysis of experimental results. Optimization was carried out by using the desirability function and genetic algorithm. A multiple regression model was used for relationship build-up.

According to desirability function, genetic algorithm and multiple regression analysis, optimal machining parameters were cutting speed 40 m/min, feed 0.2 mm/rev and depth of cut 0.50 mm, which resulted in minimal specific energy consumption of 0.78, 0.772 and 0.78 kJ/mm³, respectively. Correlation analysis and multiple regression model found a quadratic relationship between specific energy consumption with power consumption and material removal rate.

In the past, many researchers have developed mathematical models for specific energy consumption, but these models were developed at high cutting speed, and a majority of the models were based on the material removal rate as the independent variable. This research work developed a mathematical model based on the machining parameters as an independent variable at low cutting speeds, for a new type of large-sized hardened alloy steel roll. A multiple regression model was developed to build a quadratic relationship of specific energy consumption with power consumption and material removal rate. This work has a practical application in hot rolling industry.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.

The paper aims to explore the relationship between accounting and racial violence through an investigation of sharecropping in the postbellum American South.

A range of primary sources including peonage case files of the US Department of Justice and the archives of the National Association for the Advancement of Colored People (NAACP) are utilised. Data are analysed by reference to Randall Collins' theory of violence. Consistent with this theory, a micro-sociological approach to examining violent encounters is employed.

It is demonstrated that the production of alternative or competing accounts, accounting manipulation and failure to account generated interactions where confrontational tension culminated in bluster, physical attacks and lynching. Such violence took place in the context of potent racial ideologies and institutions.

The paper is distinctive in its focus on the interface between accounting and “actual” (as opposed to symbolic) violence. It reveals how accounting processes and traces featured in the highly charged emotional fields from which physical violence could erupt. The study advances knowledge of the role of accounting in race relations from the late nineteenth century to the mid-twentieth century, a largely unexplored period in the accounting history literature. It also seeks to extend the research agenda on accounting and slavery (which has hitherto emphasised chattel slavery) to encompass the practice of debt peonage.

This paper introduces the special issue on Race and Accounting and Accountability. In so doing, it explores racism in its historical and contemporary forms, the role of accounting and accountability in enabling racism and racial discrimination and also efforts of redress and resistance.

We reflect on several critical themes to demonstrate the pervasive and insidious nature of racism and, review the literature on race and racism in accounting, focusing on studies that followed the seminal work by Annisette and Prasad (2017) who called for more research. We also review the six papers included in this special issue.

While many overt systems of racial domination experienced throughout history have subsided, racism is engrained in our everyday lives and in broader societal structures in more covert and nuanced forms. Yet, in accounting, as Annisette and Prasad noted, the focus has continued to be on the former. This special issue shifts this imbalance – five of the six papers focus on contemporary racism. Moreover, it demonstrates that although accounting technologies can and do facilitate racism and racist practices, accountability and counter accounts offer avenues for calling out and disrupting the powers and privileges that underlie racial discrimination and, resistance by un-silencing minority groups subjected to discrimination and injustice.

This introduction and the papers in the special issue offer rich empirical and theoretical contributions to accounting and accountability research on race and racial discrimination. We hope they inspire future race research to nurture progress towards a true post-racial society.

This paper aims to investigate the extent to which nostalgic advertising can foster brand love. It examines the effects of two common forms of nostalgia in advertising – that is, personal and historical nostalgia – on consumers’ love towards a brand in both a developed (the UK) and a developing country (India).

A pre-test and post-test quasi-experimental study was conducted with two representative samples of consumers (i.e. 277 British and 255 Indian). Respondents were randomly exposed to one ad evoking either personal or historical nostalgia, or a non-nostalgic ad.

The results indicate that the use of nostalgia in advertising increases brand love in both countries. However, the effectiveness of each type of nostalgia varies depending on the country considered. In the UK, personal nostalgia increases brand love more than historical nostalgia, whereas, in India, historical nostalgia was found to be more significantly related to brand love than personal nostalgia.

The primary implication for marketers is to consider nostalgic advertising as a critical lever to building longer-term value for a brand (i.e. brand love) whilst being mindful of the country-specific differences regarding how such a lever should be executed to achieve effectiveness be effective.

The paper contributes to the advancement of the brand love literature by clarifying whether, and under what circumstances, the use of specific types of nostalgia in advertising increases consumers’ love towards a brand.

This study aims to reveal the influence of milling process parameters on the surface roughness and morphology of superalloy GH4145.The groove milling mechanism and surface quality influence factors of superalloy GH4145 were studied experimentally.

This paper provides investigations on three-dimensional finite element model (FEM) and simulation of milling process for GH4145.The milling experiment uses Taguchi L16 experimental design and single factor experimental design. The surface morphology of the workpiece was observed by scanning electron microscopy, and the influence mechanism of milling parameters on surface quality is expounded.

The results show that the cutting force increases by 133% with the increase in milling depth. The measured minimum surface roughness is 0.035 µm. With the change in milling depth, the surface roughness increases by 249%. With the change in cutting speed, the surface roughness increased by 54.8%. As the feed rate increases, the surface roughness increases by a maximum of 91.1%. The milling experiment verifies that the error between the predicted surface roughness and the actual value is less than 8%.

The milling experiment uses a Taguchi L16 experimental design and a single-factor experimental design. Mathematical models can be used in research as a contribution to current research. In addition, the milling cutter can be changed to further test this experiment. Reveal the influence of milling process parameters on the surface roughness and morphology of superalloy GH4145.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0080/

Online learning gained ground during the pandemic and has continued to be used in the post-Covid era. Items related to online learning should be included in service quality assessment. The purpose of this study is to examine the influence of service quality, which includes the online learning dimension, on student satisfaction in higher-education in a blended learning environment.

A total of 452 valid questionnaires were collected from business undergraduate students enrolled in public universities in Greece. A modified version of HEdPERF is used to evaluate service quality. Due to the extensive use of online learning, an additional dimension was added to the HEdPERF scale which focuses on online education, a field that has not yet been widely examined. Structural equation modeling is used to examine the relationships between service quality, and student satisfaction.

The research findings verify the six-structure scale of the HEdPERF instrument (non-academic aspects, academic aspects, reputation, access and programs issues and online learning), providing satisfactory results in terms of reliability and validity tests. Service quality dimensions such as academic aspects, access, program issues and online learning are the influential dimensions of student satisfaction in a blended learning context.

To the best of the authors’ knowledge, no previous study has expanded traditional service quality instruments to include the dimension of service quality of online learning.

The purpose of this study is to explore the complex interplay between technology, personal norms and emotional factors in shaping the sustainable housing choices of millennials in emerging economies. It integrates the model of goal-directed behavior, technology acceptance model and norm activation model, incorporating both self-interest and prosocial motivations. Key adaptations involve replacing perceived behavioral control with financial self-efficacy and substituting hedonic motivation for anticipated positive emotions. Moreover, it introduces location as a practical anchor.

A quantitative, cross-sectional and descriptive research design was used in this study. Data were gathered from a sample of 610 millennial residential real estate investors across Indian smart cities. A multistage stratified sampling technique was used to ensure a representative sample. For data analysis, partial least squares structural equation modeling was used. The analysis focused on hypothesis testing to examine the relationships between the constructs of interest. Bootstrap t-values and effect sizes were used to assess the significance and magnitude of these relationships, respectively.

One of the key findings of this study was the establishment of significant positive relationships between awareness of consequences, ascription of responsibility and personal norms with behavioral intentions. This underscored the importance of personal ethical considerations in shaping intentions. Perceived usefulness and ease of use were found to significantly influence attitudes positively, highlighting the relevance of these factors in forming favorable attitudes toward behaviors. Attitude, subjective norms, financial self-efficacy and location played significant positive roles. However, negative anticipated emotions decreased desire. This illustrated the complex role emotions play in motivational processes. The study also revealed that subjective norms did not significantly contribute to shaping personal norms. This indicated a potential decoupling of societal expectations from personal ethical obligations in the decision-making process.

This study offers actionable insights for both policymakers and real estate developers. For policymakers, the findings highlight the need to craft initiatives that go beyond mere awareness, instead fostering a deep sense of personal responsibility and environmental stewardship among potential homebuyers. For real estate developers, the emphasis on financial self-efficacy and location suggests a strategy shift toward designing sustainable homes that not only meet environmental standards but also align with buyers’ financial confidence and geographic preferences. Together, these strategies can drive a more widespread adoption of sustainable housing, making sustainability a tangible and appealing choice for millennials.

To the best of the authors’ knowledge, this empirical research study was one of the first studies that contributed to the literature by integrating the model of goal-directed behavior, technology acceptance model and norm activation model. This study thus offered a nuanced understanding of the interplay between normative influences, usability perceptions, ethical considerations and emotions in the context of behavioral intentions.