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To redesign the spare parts (MRO) inventory management at Company XYZ's warehouse, considering the conditions after the COVID-19 pandemic.

To address this research project, the authors integrated three methodologies: action research, Lean Six Sigma (DMAIC) and Cross Industry Standard Process for Data Mining. These methodologies integrated the Lean Six Sigma (LSS) 4.0 framework applied in this project.

The spare parts inventory value was reduced by 15%, and inventory turnover increased by 120% without negatively impacting the internal service level.

Practitioners leading or participating in continuous improvement projects (CIPs) should consider data quality (data available and data trustworthiness), problem-solving approach and target area involvement to achieve CIP goals. Otherwise, the LSS 4.0 could fail or extend its duration by several weeks or months.

This project shows the importance of controlling a target area before deciding to conduct a LSS 4.0 project. To address this problem, the LSS 4.0 team implemented 5S during the measure phase of the DMAIC. Also, this project offers significant practitioner and theoretical contributions to the body of knowledge about LSS 4.0.

This study explores the implementation of sustainable finance in an Indonesian state-owned bank (“ABC Bank” or “ABC”). A case study approach is employed to deeply analyze the implementation using data collected through interviews and through a review of company documents. The frameworks from Soppe (2004) and Indonesia Regulation POJK 51 were used to examine the sustainable finance implementation. The findings show that ABC Bank exercises a sustainability commitment in implementing sustainable finance long before the government regulation is imposed on several banks as early adopters in Indonesia. The regulation requires selected banks to apply the eight principles of sustainable finance and prepare a sustainable financial action plan and sustainability report. ABC’s commitment is mainly driven by its status as a government-owned bank, thus facilitating the awareness of achieving public welfare while maintaining profitability. Social implication of this study is that developing countries often face more severe consequences of climate change than developed countries. Hence, the sustainable finance implementation can have a significant social impact to reduce the negative effect. This study contributes to the literature by exploring the initial adoption of sustainable finance by a state-owned bank attempting to balance the interests of the public and management. It also provides insights into other financial institutions adopting sustainable finance as mandated by the local obligation POJK 51.

This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.

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.

Does the simultaneous vertical and horizontal alignment of HR systems positively impact innovation? The authors use the “innovation value chain” model to explore the interplay between the central strategic human resource management concepts of vertical and horizontal fit of HR systems and their role in positively impacting product innovation management.

The authors use the findings from a case study of a large multinational organization in the high-tech sector for the present study. In the first phase, the authors analyse responses to 20 qualitative interviews with senior business and HR executives at the organization using the grounded theory approach. In the second phase, the authors analysed six years of performance ratings and salary data for 4,500–5,500 employees.

Phase 1 of the study established the importance of innovation management as a strategic priority and the role of vertical and horizontal fit of HR systems and practices in positively impacting innovation management. Phase 2 reinforced the findings from Phase 1 by demonstrating the vertical and horizontal fit of the performance and compensation management processes towards furthering innovation management. Our study findings suggest that both forms of fit boost innovation management and interact to reinforce each other mutually, magnifying their respective positive effects towards improving innovation management.

While past studies have generally focused on the isolated role of either the HR system or that of a bundle of HR practices on innovation, the present study empirically demonstrates the simultaneous role of vertical and horizontal fit of HR systems and practices in furthering innovation management. The authors use interviews with senior executives and objective performance and salary data to provide the first experimental evidence of the mechanism of the interplay between the two forms of fit.

The primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.

This study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.

It was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.

This study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.

Assembly lines are widely employed in manufacturing processes to produce final products in a flow efficiently. The simple assembly line balancing problem is a basic version of the general problem and has still attracted the attention of researchers. The type-I simple assembly line balancing problems (SALBP-I) aim to minimise the number of workstations on an assembly line by keeping the cycle time constant.

This paper focuses on solving multi-objective SALBP-I problems by utilising an artificial bee colony based-hyper heuristic (ABC-HH) algorithm. The algorithm optimises the efficiency and idleness percentage of the assembly line and concurrently minimises the number of workstations. The proposed ABC-HH algorithm is improved by adding new modifications to each phase of the artificial bee colony framework. Parameter control and calibration are also achieved using the irace method. The proposed model has undergone testing on benchmark problems, and the results obtained have been compared with state-of-the-art algorithms.

The experimental results of the computational study on the benchmark dataset unequivocally establish the superior performance of the ABC-HH algorithm across 61 problem instances, outperforming the state-of-the-art approach.

This research proposes the ABC-HH algorithm with local search to solve the SALBP-I problems more efficiently.

This study aims to evaluate the quality of information recorded in Behaviour Monitoring Charts (BMC) for Behaviours that Challenge (BtC) in dementia in an older adult inpatient dementia service in the North of England (Aim I) and to understand staff perceptions and experiences of completing BMC for BtC in dementia (Aim II).

Descriptive statistics and graphs were used to analyse and interpret quantitative data gathered from BMC (Aim I) and Likert-scale survey responses (Aim II). Thematic analysis (Braun and Clarke, 2006) was used to analyse and interpret qualitative data collected from responses to open-ended survey questions and, separately, focus group discussions (Aim II).

Analysis of the BMCs revealed that some of the data recorded relating to antecedents, behaviours and consequences lacked richness and used vague language (i.e. gave reassurance), which limited its clinical utility. Overall, participants and respondents found BMC to be problematic. For them, completing BMCs were not viewed as worthwhile, the processes that followed their completion were unclear, and they left staff feeling disempowered in the systemic hierarchy of an inpatient setting.

Functional analysis of BMC helps identify and inform appropriately tailored interventions for BtC in dementia. Understanding how BMCs are used and how staff perceive BMC provides a unique opportunity to improve them. Improving BMC will support better functional analysis of BtC, thus allowing for more tailored interventions to meet the needs of people with dementia.

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.