Search results

This study addresses the prevailing complexities and limitations in estimating and managing construction overhead costs (COCs) in the existing literature, with the purpose of enhancing the accuracy of cost performance indicators in construction project management.

An innovative approach is proposed, employing the activity-based costing (ABC) accounting method combined with building information modelling (BIM) to assign real overhead costs to project activities. This study, distinguished by its incorporation of a real case study, focuses on an administrative building with a four-story concrete structure. It establishes an automated method for evaluating project cost performance through the detailed analysis of earned value management (EVM) cost indicators derived from ABC results and BIM data.

The results show that the ABC integration improves the accuracy of cost performance indicators by over 9%, revealing the project's true cost index for the first time and demonstrating the substantial value of the approach in construction engineering and management.

The current study highlights a notable gap in the existing literature, addressing the challenges in onsite overhead cost estimation and offering a solution that incorporates the state-of-the-art techniques.

The proposed method has significant implications for project managers and practitioners, enabling better-informed decisions based on precise cost data, ultimately leading to enhanced project outcomes.

This research uniquely combines ABC and BIM, presenting a pioneering solution for the accurate estimation and management of COCs in construction projects, adding significant value to the current body of knowledge in this field.

In the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.

A human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.

The task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.

This proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.

This study aims to explore the managerial conception of the determinants and barriers of sustainability integration into management control systems (MCS) of manufacturing companies in Sri Lanka. Although existing literature has explored the factors that influence the adoption of specific management controls to handle environmental and social issues, the role of management conception has been underrepresented. Specifically, literature is scarce in identifying contextual and organisational factors that influence corporates beyond mere adoption of controls but to integrate with regular controls, especially in developing countries such as Sri Lanka.

A multiple case study approach has been used to identify the management conception of barriers and enablers for sustainability control integration. The analysis is conducted based on a theoretical framework extending the work of Gond et al. (2012) and George et al. (2016). To obtain an in-depth and multifaceted view, semi-structured interviews were conducted with managers in charge of different functional departments of five manufacturing companies.

The findings identified managers’ perceived factors, such as environmental impact, stakeholder pressure (customer, competitor and regulatory authorities) and top management commitment, showing a clear difference between strongly and weakly integrated companies. Contrary to the literature, domestic regulatory pressure and multinational ownership do not sufficiently drive MCS sustainability integration.

The findings have implications for managers and practitioners to anticipate the potential barriers and determinants of sustainability integration and provide guidance to take proper measures to deal with them when designing and implementing their MCS.

The study adds value to the literature by presenting a theoretical framework based on the triangulation of different theories to recognise the significance of management idea in sustainable integration. Furthermore, because sustainable integration of MCS is a novel idea, this research is one of the earlier attempts to highlight problems from the perspective of developing countries.

Project managers bear the responsibility of selecting and developing resource scheduling methods that align with project requirements and organizational circumstances. This study focuses on resource-constrained project scheduling in multi-project environments. The research simplifies the problem by adopting a single-project perspective using gain coefficients.

It employs uncertainty theory and multi-objective programming to construct a model. The optimal solution is identified using Matlab, while LINGO determines satisfactory alternatives. By combining these methods and considering actual construction project situations, a compromise solution closely approximating the optimal one is derived.

The study provides fresh insights into modeling and resolving resource-constrained project scheduling issues, supported by real-world examples that effectively illustrate its practical significance.

The research highlights three main contributions: effective resource utilization, project prioritization and conflict management, and addressing uncertainty. It offers decision support for project managers to balance resource allocation, resolve conflicts, and adapt to changing project demands.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

As the tourism industry emerges from full or partial closure caused by the COVID-19 crisis, it is imperative to understand the internal conditions that assisted organizations to maintain positive employee attitudes despite the adverse effects of unpopular cost–retrenchment strategies. Therefore, this study aims to understand the impacts of transformational leadership (TFL), human resource management (HRM) crisis cost–retrenchment and ethical climate (EC) on employee job outcomes affected by COVID-19 pandemic.

Mid-level managers of service organizations from a travel destination heavily reliant on the tourism participated in an online self-administered survey one month after the state eased its COVID-19 travel restrictions. Partial least square structural equation modeling (PLS-SEM) examined how TFL and EC influenced cost–retrenchment crisis–management HRM, satisfaction and trust in the organization, followed by PLS multi-group analysis (PLS-MGA) to understand differences between hospitality and non-hospitality employees.

Results revealed an overall positive effect of TFL that diminished the negative affect of HRM cost-retrenchment on employee satisfaction. PLS-MGA showed a significant positive role of other-focused EC on employee outcomes, especially for hospitality organizations, whereas self-focused EC had a negative impact for non-hospitality firms.

This study contributes to contingency theory of leadership by demonstrating that TFL in combination with EC mitigates or overpowers the negative effects of cost–retrenchment crisis management strategies on employees. The study advances knowledge of self-focused and other-focused moral reasoning climate impacts under COVID-19 conditions for hospitality organizations. The industry comparison results highlight the important positive characteristics of hospitality crisis management.

This research aimed to measure the influence of resource dependency (trading and/or shareholder's dependencies) squad age structure by building archetypes to identify strategic dominant schemes.

Based on the Ligue 1 football clubs from the 2009/2010 season to the 2018/2019 data, the authors use the k-means classification to build archetypes of resource dependency and squad structure variables. The influence of resource dependency on squad structure is then analysed through a table of contingency.

Firstly, the authors identify archetypes of resource dependency with some clubs that are dependent on the transfer market and others that do not count on sales to balance their account. Secondly, they provide different archetypes of squad structure choices. The contingency between those archetypes allows to identify three main strategic schemes (avoidance, shaping and adaptation).

The research tests an original relationship between resource dependency of clubs and their human resource strategy to respond to it. This paper can help to provide detailed profiles for big clubs looking for affiliate clubs to know which clubs have efficient academy or player development capacities.

Industry 4.0 defines the application of digital technologies on business infrastructure and processes. With the increasing need to take into account the social and environmental impact of technologies, the concept of Society 5.0 has been proposed to restore the centrality of humans in the proper utilization of technology for the exploitation of innovation opportunities. Despite the identification of humans, resilience and sustainability as the key dimensions of Society 5.0, the definition of the key factors that can enable Innovation in the light of 5.0 principles has not been yet assessed.

An SLR, followed by a content analysis of results and a clustering of the main topics, is performed to (1) identify the key domains and dimensions of the Industry 5.0 paradigm; (2) understand their impact on Innovation 5.0; (3) discuss and reflect on the resulting implications for research, managerial practices and the policy-making process.

The findings allow the elaboration of a multileveled framework to redefine Innovation through the 5.0 paradigm by advancing the need to integrate ICT and technology (Industry 5.0) with the human-centric, social and knowledge-based dimensions (Society 5.0).

The study detects guidelines for managers, entrepreneurs and policy-makers in the adoption of effective strategies to promote human resources and knowledge management for the attainment of multiple innovation outcomes (from technological to data-driven and societal innovation).

This study aims to examine the impact of intellectual capital (IC) on default risk in Indian companies listed on the National Stock Exchange.

This study applies panel data regression analysis to derive a relationship between IC and default risk for the sample period 2013–2022. The value-added intellectual coefficient (VAIC) of Pulic (2000) has been applied to measure IC performance, and default risk is estimated using the revised Z-score model of Altman (2000).

The results revealed a positive association between Z-score and VAIC. It implies that a higher value of VAIC improves financial stability and leads to a lower likelihood of default. The findings further suggest that new default forecasting models can be experimented with IC indicators for better default prediction.

The findings can have implications for investors and banks. This paper provides evidence of IC performance in improving the financial solvency of firms. Investors and financial institutions should invest their resources in a healthy firm that effectively manages and invests in their IC. It will eventually award investors and creditors high returns through efficient value-creation processes.

This study provides evidence of IC performance in improving the financial solvency of Indian high-defaulting firms, which lacks sufficient evidence in this domain of research. Numerous studies exist examining the relationship between firm performance and IC value, but this area is inadequately focused and underresearched. This study, therefore, fills the research gap from an Indian perspective.

This study aims to reveal to what extent successful European listed firms depend on their intellectual capital investment in achieving business success during the global financial crisis.

This study used value added intellectual coefficient (VAIC) methodology to measure the effect of intellectual capital on financial performance of business, which consist of 683 the sample listed firms. To examine the nexus between intellectual capital, legal origin and firm performance, estimated panel test and ordinary least squares regression model is used to data obtained from a sample of European countries.

The finding of this study suggests that there exists a positive relationship between intellectual capital and firm performance with return on assets (ROA) before the financial crisis, while firm performance with return on equity did not contribute to intellectual capital before and after the crisis period. Additionally, common law countries have a positive and statistically significant impact on firm performance with ROA for the before-crisis period, while code law countries have positively significant effect with VAIC on ROA.

The VAIC method has played a critical role in the management decision-making process to integrate the intellectual capital in the financial crisis period.

This study examines intellectual capital components such as human capital, structural capital and process capital efficiencies and firm performance in the legal origin context. The empirical evidence shows that there are significant impacts of legal origin on the nexus between intellectual capital and performance of listed firms during the global financial crisis.