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This study aims to understand the role of drivers, underlying challenges and, consequently, the implications of the reverse knowledge transfer (RKT) process for the multinational enterprises (MNE)s.

A dyadic qualitative research design was used with a cross-country design covering perspectives from both the headquarters and subsidiaries from the USA, Denmark, Pakistan, India and Bangladesh. In-depth interviews were conducted with managers in multiple sectors such as information technology, telecommunications, project management and engineering.

The study reveals the constraints and drivers of the RKT process, and furthermore elaborates on the implications for MNEs. RKT can lead to the development of new processes, subsidiary independence and intra-organizational knowledge transfer. Besides, it can entail challenges such as position insecurity for subsidiaries and a blurring of the MNE market vision. The findings demonstrate several implications for the MNEs.

The study highlights the direct implications of RKT for the multinational enterprises. The findings serve as a practical guide for global managers seeking to improve their competitive edge.

The study presents a framework of the RKT process from emerging market subsidiaries to parent companies, that demonstrates the role of drivers, underlying challenges and implications of the RKT process for the MNEs.

The purpose of this paper is to examine small and medium-sized enterprises’ (SMEs) level of participation in human resource development activities during a labor shortage. Drawing on human capital theory, it examines whether SMEs’ profiles, determined according to their participation in different types of training activities, relate to perceived benefits of training, barriers to participation in training and learning culture.

This study applies latent profile analysis (LPA) to 10 training practices of 427 SMEs in Quebec, Canada.

The LPA distinguished four profiles of SMEs, reflecting differing capacities for mobilizing training resources during a labor shortage. These four profiles show differences with regard to perceived training benefits, barriers to participation in training and learning culture.

To the best of the authors’ knowledge, this study is among the first to focus on the specific ability of SMEs to invest in their human capital in the unique and recent context of a labor shortage.

The current study aims to analyze the linkage among bank competition, liquidity and loan price in an interconnected bank network system.

The study employs the Lerner index to estimate bank power; Granger non-causality for estimating competition, liquidity and loan price network structure; principal component for developing competition network index, liquidity network index and price network index; and panel VAR and LASSO-VAR for analyzing the dynamics of interactive network effect. Current work considers 33 Indian banks, and the duration of the study is from 2010 to 2020.

Network structures are concentrated during the economic upcycle and dispersed during the economic downcycle. A significant interaction among bank competition, liquidity and loan price networks exists in the Indian banking system.

The study meaningfully contributes to the existing literature by adding new insights concerning the interrelationship between bank competition, loan price and bank liquidity networks. While enhancing competition in the banking system, the regulator should also pay attention toward making liquidity provisions. The interactive network framework provides direction to the regulator to formulate appropriate policies for managing competition and liquidity while ensuring the solvency and stability of the banking system.

The study contributes to the limited literature concerning interactive relationship among bank competition, liquidity and loan price in the Indian banks.

In this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of data (LAD) and ant colony optimization (ACO) algorithms in extracting patterns of high impact loads and normal loads from historical railway records. In addition, the patterns are employed in establishing a classification model used for classifying unseen observations. A case study representing real-world impact load data is presented to illustrate the impact of the proposed approach in improving railway services.

Application of artificial intelligence and machine learning approaches becomes an essential tool in improving the performance of railway transportation systems. By using these approaches, the knowledge extracted from historical data can be employed in railway assets monitoring to maintain the assets in a reliable state and to improve the service provided by the railway network.

Results achieved by the proposed approach provide a prognostic system used for monitoring the conditions surrounding rail wheels. Incorporating this prognostic system in surveilling the rail wheels indeed results in better railway services as trips with no-delay or no-failure can be realized. A comparative study is conducted to evaluate the performance of the proposed approach versus other classification algorithms. In addition to the highly interpretable results obtained by the generated patterns, the comparative study demonstrates that the proposed approach provides classification accuracy higher than other common machine learning classification algorithms.

The methodology followed in this research employs ACO algorithm as an artificial intelligent technique and LDA as a machine learning algorithm in analyzing wheel impact load alarm-collected datasets. This new methodology provided a promising classification model to predict future alarm and a prognostic system to guide the system while avoiding this alarm.

Social factors can shape economic decisions. Corporate governance (CG) studies and guidelines usually neglect that the chief executive officer (CEO) and board members may be socially tied. This study investigates the effects of social ties between the CEO and board members on earnings management (EM).

The authors run a series of regressions using a sample of Brazilian companies listed on the Brazilian Stock Exchange [B]³ between 2011 and 2017 to assess the effect of the social ties between the CEO and board members on EM using a social ties index. The authors also employ five robustness tests to verify the consistency of results, including alternative proxies of EM and social ties and an estimation using fixed effects.

After developing and computing a social ties index between the CEOs and members of the board of directors (BD) and the fiscal council (FC), the study’s findings indicate that a significant level of social ties between the CEO and BD has a negative impact on EM. However, for FC members, the authors found non-significant results.

Unlike previous studies, the authors built a social tie index (STI) from five elements of social ties assessed in an environment with a two-tier board system. Results show that elements of social interactions and personal relationships can benefit the company, as a CEO's level of social ties with the BD reduces EM practices.

This paper examines the theoretical issues and research themes of business and management impact. Our empirical setting is the UK Research Excellence Framework 2014 (REF 2014) and the focus is on the nature of research impact. Stakeholders, including Governments, now expect academic outputs to translate to real world benefits beyond the narrow bibliometric type metrics.

Despite decades of academic literature devoted to business and management research impact, current theories cannot explain the apparent disconnect between academic, economic and societal practice. Adopting a UK Business and Management perspective to frame our investigation, we consider the highly contested rhetorical question – What are the current themes and impacts of Business and Management research?

We propose a definition for research impact and consider its measurement. Then, using the 410 Impact Case Studies submitted to REF 2014 #x2013; Unit of Assessment 19, business and management, we examine how high impact unfolds. The implications for business and management research impact from the perspectives of economic, knowledge and responsibility impacts are considered.

The crude oil supply chain (COSC) is one of the most complex and largest supply chains in the world. It is easily vulnerable to extreme events. Recently, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (often known as COVID-19) pandemic created a massive imbalance between supply and demand which caused significant price fluctuations. The purpose of this study is to explore the influential factors affecting the international COSC in terms of consumption, production and price. Furthermore, it develops a model to predict the international crude oil price during disease outbreaks using Random Forest (RF) regression.

This study uses both qualitative and quantitative approaches. A qualitative study is conducted using a literature review to explore the influential factors on COSC. All the data are extracted from Web sources. In addition to COVID-19, four other diseases are considered to optimize the accuracy of predictive results. A principal component analysis is deployed to reduce the number of variables. A forecasting model is developed using RF regression.

The findings of the qualitative analysis characterize the factors that influence international COSC. The findings of quantitative analysis emphasize that production and consumption have a higher contribution to the variance of the data set. Also, this study found that the impact caused to crude oil price varies with the region. Most importantly, the model introduced using the RF technique provides a high predictive ability in short horizons such as infectious diseases. This study delivers future directions and insights to researchers and practitioners to expand the study further.

This is one of the few available pieces of research which uses the RF method in the context of crude oil price forecasting. Additionally, this study examines international COSC in the events of emergencies, specifically disease outbreaks using machine learning techniques.

The built environment is a complex sector that demands coordination and cooperation of stakeholders. Construction projects from the complex sector require skills, services, and integration of major disciplines in the built environment. Sustainability of the major disciplines' standards regarding the appropriateness of the built environment tertiary education cannot be over-emphasised in Nigeria. Studies concerning Nigeria's built environment programmes accreditation (BEPA) in the 21st-century education system are scarce. Thus, the study investigated the relevance and perceived factors hindering Nigeria's BEPA in the 21st-century education system. Also, the study proffered measures to improve Nigerian built environment tertiary education accreditation ranking.

Data were sourced from elite virtual interviews across Nigeria. The interviewees were knowledgeable about Nigeria's built environment programmes accreditation, and many of them have been directly or indirectly involved. The investigators utilised a thematic analysis for the collated data and enhanced it with secondary sources.

The study revealed that several Nigerian academia in the built environment lack fame in research, publication, and citations due to barriers in their workplace. It has hindered their global institution's accreditation and ranking standards. Findings identified inadequate basic infrastructure, obsolete curricula, lack of research novelty, lack of higher education institutions funding, inadequate staffing and lax upskilling and reskilling, and unethical practices “systematic corruption” as major factors hindering BEPA. Also, findings proffered measures to improve Nigeria's BEPA global ranking.

The study is limited to the perceived barriers and measures to improve BEPA in the 21st-century in Nigeria via semi-structured virtual interviews. Future study is needed to validate the findings as highlighted in the thematic network.

The paper confirms that the BEPA requires innovative and multidisciplinary measures to improve the global ranking of these programmes and, by extension, the higher education institutions ranking globally. The paper would stir major stakeholders and advance the built environment programmes quality accreditation regarding international best practices and maintain the minimum standards.

The paper comprehensively analyses the perceived factors and proffered measures to improve Nigeria's BEPA in the 21st-century via a thematic network. The outcome intends to improve the global ranking and stir stakeholders to reposition and showcase Nigeria's built environment programmes to the world.

Safety and security (S&S) are critical concerns in South Africa, especially in Cape Town, one of the country’s most crime-ridden cities. The University of Cape Town (UCT), situated on a large, open campus, has experienced increased malefaction. Facilities management (FM) services at universities bear the primary responsibility for providing S&S to their communities. To comprehensively understand and address the community’s demands regarding S&S, the current study was conducted to investigate the challenges specific to open universities. This study aims to determine whether implementing community-based FM (CbFM) principles and using technological innovations could offer a more effective and sustainable solution.

The study adopted interpretivist overarching case study methodology, which is ontologically based. A mixed-method approach was used to incorporate the strengths and limitations of the weaknesses of both methods. The data collection took the form of an online survey of the university community and semi-structured interviews with university executive management to obtain data from the single case study of UCT. Descriptive statistics were used to analyze the quantitative data, and thematic analysis was used to identify emergent themes from the qualitative data.

The study presents an overall view of the provision of S&S at UCT, the unique challenges faced by management and the main S&S issues affecting the community. Moreover, the study reveals that UCT has implemented community participation processes in the past with limited success. This is because the strategies implemented constitute a narrow perspective of community participation. Therefore, a much smarter and more inclusive perspective using technological innovation is required for successful community participation to occur and to be successfully used in providing S&S toward achieving future-proofing facilities.

This research has demonstrated the influence of CbFM and innovative technologies on the S&S of the open campus. Hence, future-proof facilities can be achieved when FM actively engages university communities in managing campuses through technological innovation.