Search results

1 – 5 of 5
Open Access
Article
Publication date: 28 July 2023

Karunamunige Sandun Madhuranga Karunamuni, Ekanayake Mudiyanselage Kapila Bandara Ekanayake, Subodha Dharmapriya and Asela Kumudu Kulatunga

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process…

Abstract

Purpose

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

Design/methodology/approach

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

Findings

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

Originality/value

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

Details

International Journal of Industrial Engineering and Operations Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2690-6090

Keywords

Article
Publication date: 6 March 2023

Punsara Hettiarachchi, Subodha Dharmapriya and Asela Kumudu Kulatunga

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical…

Abstract

Purpose

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

Design/methodology/approach

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

Findings

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

Research limitations/implications

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

Originality/value

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

Details

Journal of Global Operations and Strategic Sourcing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5364

Keywords

Article
Publication date: 23 August 2022

Namal Bandaranayake, Senevi Kiridena and Asela K. Kulatunga

Achieving swift and even flow of cargo through the border, the ultimate objective of cross-border logistics (CBL) requires the close coordination and collaboration of a multitude…

Abstract

Purpose

Achieving swift and even flow of cargo through the border, the ultimate objective of cross-border logistics (CBL) requires the close coordination and collaboration of a multitude of stakeholders, as well as optimally configured systems. To achieve and sustain competitiveness in a dynamic international trade environment, CBL processes must undergo periodic analysis, improvement and optimization. This study aims to develop a modelling framework to capture CBL processes for analysis and improvement.

Design/methodology/approach

Relying on the extant literature, a meta-model is developed incorporating significant perspectives required to model CBL processes. Popular process modelling notations are evaluated against the meta-model and their ease of comprehension is also evaluated. The selected notation through evalution is augmented with addendums for a comprehensive depiction of CBL processes.

Findings

The capacity of role activity diagrams (RADs) to depict all perspectives, including interactions in a single diagram, makes them particularly suitable for modelling CBL processes. RADs have been complemented with physical flow diagrams and methods to capture temporal dimension, enabling a comprehensive view of CBL processes laying the foundation for insightful analysis.

Research limitations/implications

The meta-model developed in this paper paves the way to develop an analysis framework which requires further research.

Originality/value

The lack of well-accepted modelling notations for studying CBL processes prompts researchers to search and adapt different formalisms. This study has filled this gap by proposing a comprehensive modelling framework able to capture CBL processes at different granularities in rich detail. Not only does the developed meta-model aid in selecting the notation, it is also useful in analysing the constituent elements of CBL processes.

Details

Journal of Global Operations and Strategic Sourcing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5364

Keywords

Article
Publication date: 25 January 2024

Scott J. Niblock

This study aims to establish the effect of environmental, social and governance (ESG) practices on Australian energy and utility investment performance.

Abstract

Purpose

This study aims to establish the effect of environmental, social and governance (ESG) practices on Australian energy and utility investment performance.

Design/methodology/approach

Conventional and ESG-rated portfolios are constructed using monthly returns and ESG scores of S&P/ASX 300 listed energy and utility firms from 2014 to 2022. Portfolio performance is estimated using a four-factor regression model, controlling for any economic shocks associated with the COVID-19 pandemic.

Findings

The findings show that the lower the ESG score associated with the overall ESG and environmental portfolios, the greater the performance compared to the market (but not the conventional and other ESG portfolios). High ESG scores do not appear to influence the performance of the energy and utility portfolios, which contrasts expectations that the uptake of ESG should deliver superior risk-return outcomes for investors. The findings also indicate that a contrarian investment approach may be a reasonable performance indicator for high-rated ESG portfolios. ESG practices did not impact portfolio performance during the COVID-19 pandemic.

Originality/value

This research has contributed to the literature by offering ESG investment insights for policymakers, regulators, fund managers and investors. Consistent with the agency perspective on ESG practices and efficient market hypothesis, the evidence implies that, regardless of ESG scores (either high or low), investors should consider investing passively in diversified energy and utility portfolios or low-cost index fund equivalents.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 20 November 2023

Fatemeh Saeedi, Mahdi Salehi and Nour Mahmoud Yaghoubi

Financial reports are the basis of economic decisions that affect organizational interests and shareholders. However, there is a severe research gap concerning the factors…

Abstract

Purpose

Financial reports are the basis of economic decisions that affect organizational interests and shareholders. However, there is a severe research gap concerning the factors affecting the quality of financial information (such as audit report readability and tone). Therefore, considering the importance of presenting high-quality financial information, this study aims to investigate the impact of intellectual capital (IC) and its components on the audit report's readability and tone.

Design/methodology/approach

The multivariate regression model tests research hypotheses. Then, hypotheses are tested via a sample of 824 observations of the listed companies on the Tehran Stock Exchange (103 companies) from 2014 to 2021, using the multivariate regression model based on pooled data and fixed effects.

Findings

Results determine that customer capital (CC) and structural capital (SC) are likely to influence the audit report tone positively. In general, the IC and human capital (HC) negatively impact auditors' tone. More analyses also document that IC and its CC, HC and SC components positively and significantly affect audit report readability based on two readability indices, including FOG and text length. Finally, findings pertaining to the third readability index (Flesch index) reveal that only HC and SC are robust based on this measurement, whereas the IC and CC have a negative and significant impact on the readability of auditors’ reports.

Originality/value

To the best of the authors’ knowledge, this study is the first to address this issue in emerging markets, and it provides helpful insights for users, analysts and legal institutions regarding IC, which significantly affects audit report readability and tone.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

1 – 5 of 5