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This paper aims to examine the creation of the first commercial school in early independent Argentina in 1826 – the Academy of Accountancy of Buenos Aires (AABA) – at the request of the Argentine Government, which entrusted its direction to French expatriate Amédée Brodart, who was considered an expert in commercial education.

This study adopts a microhistory approach based on individual biography and archival research. First, it investigated published biographies of contemporary political figures Brodart had been in contact with. Then, the Argentine archives of the Ministry of Finance and the Arturo Jauretche Museum of the Bank of the Province of Buenos Aires provided information on Brodart’s life during his expatriation to Latin America. Finally, the French Archives of the Paris National Library and ESCP Business School in Paris provided information on Brodart’s life before his departure for Argentina and after his final return to France. These primary sources include extracts from Brodart’s correspondence, financial ledgers, study plans and a few rare iconographic documents.

AABA was connected to a nationalist agenda: to develop Argentinian trade to overcome national underdevelopment and to counter political agitation in the country. However, the lack of local expertise in commercial education, as well as Argentine authorities’ desire to avoid depending on foreign powers, led them to call on a French expatriate rather than on a network of organizations to open this school.

This paper contributes to the literature on the history of commercial education in Latin America and to the literature on the international transfer of commercial education models. This paper is also among the first to consider the origin story of Argentina’s relationship with commercial education.

This research offers new reflexive perspectives on the emergence of commercial education in Latin America by highlighting the agentivity of local actors.

Through a lens of dependency ambiguity, this paper repositions narratives of the development of commercial education in Latin America away from a Western-centric explanation, highlighting the role of local contextual actors. In doing so, it offers an alternative history of commercial education focused on Latin America.

The development of innovative learning environments at the new Viscontini primary school started with the research and development of a sense of belonging to the new building. Initially, it was indeed difficult to get used to the new, spacious learning spaces, reformulating a different teaching approach than the classic traditional method based on frontal classroom teaching. Teachers and students were therefore able to identify and deepen, thanks to the support of the National Institute for Documentation, Innovation and Educational Research (INDIRE) Institute and the University of Milan Bicocca, the fundamental relationship between all learning environments (indoor and outdoor) and a teaching approach closely linked to the diversified use of the building's spaces. All the learning environments (entrance hall, atriums, corridors, laboratories, garden, playground, etc.), which were initially bare and aseptic, were given attention, analysed, developed, filled and finally fitted out and decorated, fostering a sense of physical and mental appropriation of the new school.

The proliferation of environmental rating tools over the past two decades has endeavoured to assist the industry in measuring sustainability. Recent changes to the International Valuation Standards (IVS) have directed valuers to consider ESG. The purpose of this study aims to examine how commonly utilized sustainability tools, which have been employed to communicate building sustainability credentials, align with the IVS categories of ESG.

The research utilises the IVS categorisation of ESG and maps sustainability tools adopted at scale by the Australian Commercial Real Estate market. The approach identifies the various attributes within the commonly utilised rating tools that align with IVS defined ESG criteria.

The mapping provides insights into the coverage of the IVS ESG criteria in the mainstream tools used in Australia. Further, the research identifies existing sustainability criteria that are relevant to the built environment, that have not been clearly identified by the IVS, but have an important role in evaluating the sustainability of commercial real estate.

For investors, occupiers and valuers, this research provides insights on how the current, commonly utilised sustainability rating tools align with the IVS-defined ESG metrics. This research assists in providing greater clarity regarding the relationship between ESG criteria and existing rating tools, which have been recently identified as key considerations in valuation practice and help to provide transparency and understanding for property stakeholders.

The importance of monitoring, reporting and enhancing transparency in ESG disclosures has emerged as a central issue with significant implications for the property industry. This research provides the first evaluation of how existing sustainability rating tools map against ESG criteria as directed in the IVS.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.

Social movement organizations are concerned and cognizant of their public image and typically need to maintain positive public perception to gain and sustain support. White supremacist organizations believe that they are highly stigmatized, reviled, and surveilled groups and go to great lengths to protect their desired self-representation. Through a qualitative analysis of close to 2 million Discord chat messages from white supremacist organizations, I find that white nationalist groups attempt to cater their public appearances through three primary axes: organizational, activism, and individual/membership. This chapter uses concepts from Goffmanian sociology, such as Stigma, Impression Management, and Frontstage/Backstage, to highlight how political movements discuss, argue, and debate the public image they wish to deploy. Studies on right-wing movements tend to be “externalist” in the sense that they look at publicly available documents which privilege the views of leadership. This chapter uses a dataset which delves into the social movement “backstage,” enabling us to view white supremacists' private conversations, their impression management strategies, and how they wish to appear on the “frontstage.”

This study examines how intellectual capital (IC) drives firm performance via the lens of dynamic capabilities (DCs). Drawing on resource-based view (RBV) and dynamic capability view (DCV), the authors elaborate the mediating role of learning, integration and reconfiguration DC in the Indian banking context.

A sample of 358 top- and middle-level managers from the Indian banking sector was administered with structured questionnaires for data collection. Structural equation modeling (SEM) and Sobel test were used to analyze the data and test the hypothesized mediating effect.

The findings reveal that learning and integration DCs are key mediators in IC and banks' performance relationships in an emerging economy context. In contrast, the analysis revealed partial mediating role of reconfiguration DC. Furthermore, the learning DC has been identified as the primary mediating mechanism for transforming bank's IC into performance benefits.

This study provides an important implication for the IC and DC link by empirically developing and validating a model in the Indian banking sector and making a several contributions to the related literature. This sector needs to incorporate and strengthen their IC and DCs to attain enhanced performance in today's dynamic environment. Bank managers can use these findings to bring their knowledge-related activities to channelize specific DCs to transform banks' IC when seeking to improve overall performance. Theoretically, this study extends previous research by outlining a set of organizational elements that tend to influence firm performances with the help of IC, learning, integration and reconfigurations DCs.

Although several studies have investigated the links between IC, DC and firm performance, studies on emerging economies are scarce. This study is one of the most in-depth investigations of the relationship between IC, learning, integration and reconfiguration DCs and firm performance in an integrated framework, with a particular focus on the banking sector of an emerging economy.

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

After reading and discussing this case study, students will be able to explain the concept of diffusion of innovation and predict how the passion fruit-infused vinaigrette (PFIV) might spread throughout the Thai market; analyze the market environment for condiments in Thailand and identify specific opportunities that Preedha Vinchit and her team should consider for the successful launch of the PFIV; interpret both qualitative and quantitative data gathered by the new product development (NPD) team and discuss its implications for the product’s market strategy and development; and critique the initial launch plan proposed by Krit Anon, suggest practical strategies and calculate the break-even point necessary to meet the project’s financial goals.

During July 2023, Vinchit, product marketer at the Thani Food Institute (TFI), faced a critical decision regarding the launch of the APFIV. Developed from TFI’s patented passion fruit peel powder, the PFIV offered functional benefits and addressed the sustainable use of passion fruit resources. As COVID-19 restrictions eased, TFI’s board of advisors anticipated a successful market entry for PFIV. Anon, culinologist and chef behind PFIV’s formulation, expressed keen interest in launching it independently with a startup investment of THB 500,000 (US$14,388). Vinchit, with market research and home-use test results indicating positive consumer reception in hand, contemplated whether to proceed with a launch plan of TFI’s design or endorse Anon’s entrepreneurial venture. Critical considerations included market viability, strategic partnerships, target demographics and marketing strategies encompassing pricing, distribution and promotional campaigns. The decision hinged on maximizing PFIV’s market potential amidst Thailand’s robust condiment consumption and growing health awareness.

This case study can be used in undergraduate and graduate courses in entrepreneurship, food product development, marketing strategy, market research and innovation on topics including NPD, opportunity identification, concept testing, consumer research analysis, marketing strategy formulation, business/financial analysis and launch strategies. This case study may be more useful in the middle or later parts of a course or module when an instructor is focusing on any or all stages of the NPD process and the strategic decisions, particularly for aspiring entrepreneurs with limited resources. Additionally, students should have developed at least some preliminary understanding of qualitative and quantitative research methods. This case study has been very effective in demonstrating various organizational processes and decision-making tools, which allow students to apply strategy frameworks and systematically evaluate several alternatives.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

This study is carried out to demonstrate the computational practicalities of environmental construction economics necessary to offer early-stage cost advice. A case study of a private sector client’s development proposal is used. This is for the acquisition of a vacant freehold land of 1.2 acres brownfield site to develop a Grade A office complex with plans to achieve the BREEAM Excellent rating green building certification.

A three-stage methodology was deployed: Order of cost estimating, before life cycle costing and then development appraisal. The Order of Cost Estimate is generated using the BCIS online database, following the procedural guideline of the New Rules Measurement (NRM). The life cycle costing was carried out from an environmental perspective to explore two design options – Design A and Design B, in terms of which would offer the best value for money whilst reducing carbon emissions.

Based on the outcome of the life cycle costing computations, Design B was chosen as the advised development due to minimal differences in net present values and annual equivalents. Further evaluation of Design B, using the residual method of developmental appraisal was carried out, with all necessary assumptions made. From the extensive computations carried out, the project is considered unviable, as it reports a loss. Alternative use of the site or an alternative site is thus recommended to check if a greater return on investment is tenable.

The study narratively interweaves the application of three computational techniques that are core to offering early-stage cost advice.

Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.