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Article
Publication date: 1 February 2021

Ali Cheaitou, Sadeque Hamdan and Rim Larbi

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently…

1180

Abstract

Purpose

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.

Design/methodology/approach

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.

Findings

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.

Research limitations/implications

The vessel carrying capacity is not considered in an explicit way.

Originality/value

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

Details

Maritime Business Review, vol. 6 no. 3
Type: Research Article
ISSN: 2397-3757

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Article
Publication date: 19 May 2022

Atul Kumar Sahu, Mahak Sharma, Rakesh D. Raut, Anoop Kumar Sahu, Nitin Kumar Sahu, Jiju Antony and Guilherme Luz Tortorella

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully…

1553

Abstract

Purpose

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

Design/methodology/approach

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

Findings

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

Practical implications

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

Originality/value

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

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Publication date: 30 January 2025

Seyi S. Stephen, Ayodeji E. Oke, Clinton O. Aigbavboa, Opeoluwa I. Akinradewo, Pelumi E. Adetoro and Matthew Ikuabe

This chapter investigated tendering in stealth construction, emphasising innovative approaches and methodologies that prioritise environmental protection, safety, efficiency, and…

Abstract

This chapter investigated tendering in stealth construction, emphasising innovative approaches and methodologies that prioritise environmental protection, safety, efficiency, and aesthetics. It began with an overview of the construction industry’s tendering processes, followed by an in-depth examination of various tendering types, including competitive and negotiated methods. The study highlighted contemporary trends such as electronic tendering, Building Information Modelling (BIM), green and sustainable procurement, risk management, data analytics, artificial intelligence, lean construction practices, and blockchain technology. Moreover, with a specific focus on stealth construction, the chapter further analysed certain criteria, including building cross-section development, visibility, radio frequency emission, and countermeasures. It explored integrating functional construction systems, including environmental, safety, health, and quality management. Additionally, it discussed methods like green building, modular construction, and low-impact techniques. Lastly, the chapter emphasised the strategies to achieve environmental protection, safety, speed, economy, and aesthetics in tendering for stealth construction.

Details

Stealth Construction: Integrating Practices for Resilience and Sustainability
Type: Book
ISBN: 978-1-83608-183-8

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Article
Publication date: 24 March 2021

Ali Raza Khoso, Aminah Md Yusof, Changsaar Chai and Muhammad Aslam Laghari

The emergence of massive modern technology construction projects is seen to be a real occurrence in Pakistan’s construction industry, which in turn demands a better and systematic…

321

Abstract

Purpose

The emergence of massive modern technology construction projects is seen to be a real occurrence in Pakistan’s construction industry, which in turn demands a better and systematic way of undertaking the project. Hence, this requires capable contractors to perform the task. A plethora of research studies are carried in the past three decades on the identification of evaluation criteria of contractor’s selection, but the road of modern technology construction projects is still unpaved.

Design/methodology/approach

This study strives for the most essential but exhaustive criteria, especially for modern technology construction projects in Pakistan. A pilot survey followed by an exhaustive questionnaire survey was carried out alongside with one-on-one interactions with professional experts serving in various public organizations under public procurement department. A total of 87 attributes were analyzed, correlated, rotated and weighted using exploratory factor analysis for identification of evaluation criteria.

Findings

The study finds that for modern technology construction projects basic format of contractor’s selection attributes is not extensive. Henceforth, the most robust, comprehensive and precise assessment is required for such modern technology construction projects. Consequently, four inimitable sets of evaluation criteria groups are designed keeping in view the growing demands of public projects around the globe.

Research limitations/implications

The research work added a novel contribution in this research area which is in quest of resolutions from the past three decades. This research opens the novel avenues in the future in terms of designing the evaluation criteria while keeping the project demands and scope in mind.

Social implications

The research is a blueprint for the construction organizations and other authorities especially to those agencies involved in the modern construction technology projects. This eye-opening work will further stimulate the clients to focus on not only the designing phase but also the execution part of such advanced construction projects which turn in the successful project outcome.

Originality/value

The larger number of past studies addressed so for from the last couple of decades is very useful to a certain extend for instance for small to medium-sized traditional construction projects. This research delineates the future to call upon the most alarming future issues and consequences of selecting the traditional contractors for their advanced projects. Being premier research in this realm, the study filled the gap of evaluating the contractors inimitably compared to what was practiced in the past.

Details

Journal of Public Procurement, vol. 21 no. 1
Type: Research Article
ISSN: 1535-0118

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Article
Publication date: 3 December 2019

R. Ghasemy Yaghin and P. Sarlak

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility…

407

Abstract

Purpose

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand.

Design/methodology/approach

The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data.

Findings

Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility.

Originality/value

This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.

Details

Journal of Modelling in Management, vol. 15 no. 2
Type: Research Article
ISSN: 1746-5664

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Article
Publication date: 29 December 2022

Atul Kumar Sahu, Sri Yogi Kottala, Harendra Kumar Narang and Mridul Singh Rajput

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of…

162

Abstract

Purpose

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

Design/methodology/approach

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

Findings

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

Research limitations/implications

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

Originality/value

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

Details

Journal of Global Operations and Strategic Sourcing, vol. 17 no. 2
Type: Research Article
ISSN: 2398-5364

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Article
Publication date: 19 January 2021

Srikant Gupta, Prasenjit Chatterjee, Morteza Yazdani and Ernesto D.R. Santibanez Gonzalez

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while…

441

Abstract

Purpose

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.

Design/methodology/approach

In this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.

Findings

This research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.

Research limitations/implications

The proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.

Practical implications

The proposed model is generic and can be applied for large-scale GSC environments with little modifications.

Originality/value

No prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.

Details

Management Decision, vol. 59 no. 10
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 14 October 2024

Muhammad Anshari, Mahani Hamdan, Norainie Ahmad and Emil Ali

Recent technological developments have encouraged the United Nations to promote the adoption of digital technologies to achieve the Sustainable Development Goals (SDGs). In…

149

Abstract

Purpose

Recent technological developments have encouraged the United Nations to promote the adoption of digital technologies to achieve the Sustainable Development Goals (SDGs). In addition to initiatives from businesses, an increasing number of studies indicate that public service agencies may gain benefits from adopting digital transformation. On a global scale, policymakers are examining the integration of digital technologies, specifically artificial intelligence (AI), into public service delivery (PSD), acknowledging the potential advantages and obstacles for the public sector. Therefore, the objective of this study is to investigate the impact of AI on PSD to support the SDGs initiative.

Design/methodology/approach

The research used a qualitative approach to explore the intersection of AI, SDGs and PSD. This approach involved scrutinising relevant publications and conducting an extensive literature review. The research also used bibliographic analysis to discern patterns within the field. Findings from the literature review and bibliographic analysis contributed to identifying research trends that explore the complex relationship among AI, PSD and the SDGs. The model derived from this comprehensive review and analysis elucidates the potential of AI to enhance PSD and contribute to the achievement of the SDGs.

Findings

The bibliographic study revealed significant research trends concerning AI, PSD and SDGs through an empirical investigation of an extensive array of peer-reviewed articles. This investigation focused on how the public sector can improve its delivery of services to citizens and all stakeholders to advance the SDGs. AI holds the promise of revolutionising PSD and bolstering the SDGs. By leveraging AI’s capabilities in data analysis, automation and customisation, governments can enhance the efficiency, effectiveness and accessibility of public services. This, in turn, enables public servants to tackle more complex tasks while providing citizens with personalised and relevant experiences. Additionally, the study advocates modelling the intersection of PSD and AI to achieve sustainable development.

Research limitations/implications

The employed research methodologies, such as literature reviews and bibliographic analysis, enrich the context of AI, SDGs and PSD. They offer a comprehensive perspective, identify knowledge gaps and furnish policymakers, practitioners and academics with a conceptual framework for informed decision-making and sustainable development endeavours.

Originality/value

The study provides an agenda for AI and SDGs research on application in PSD. It emphasises varied research viewpoints, methods and gaps. This study helps researchers as well as practitioners identify subtopics, intersecting themes and new research pathways.

Details

Journal of Science and Technology Policy Management, vol. 16 no. 1
Type: Research Article
ISSN: 2053-4620

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Article
Publication date: 27 February 2023

Dhanraj P. Tambuskar, Prashant Jain and Vaibhav S. Narwane

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big…

780

Abstract

Purpose

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

Design/methodology/approach

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

Findings

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

Research limitations/implications

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

Practical implications

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

Social implications

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

Originality/value

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

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Article
Publication date: 19 July 2024

Lan Wang, Hua Song, Yudong Yang and Mengwei Han

Previous literature reviews mainly focus on green supply chain, however, there is surprisingly little effort made in the systematic literature review to focus on a specific…

273

Abstract

Purpose

Previous literature reviews mainly focus on green supply chain, however, there is surprisingly little effort made in the systematic literature review to focus on a specific function of green supply chain, i.e. green procurement (GP). Regarding research methodology, most reviews are qualitative and inductive generalizations. Quantitative methods such as bibliometrics have started to be applied in recent years. This paper responds to this trend by counting the largest amount of literature with 238 articles in the last 24 years from 2000 to 2023 to visually analyze different theoretical perspectives and research topics into a comprehensive framework and identify future research directions and opportunities in the GP field.

Design/methodology/approach

Based on CiteSpace and in-depth content analysis, this paper attempts to visually analyze 238 valid papers to identify key literature and analyze the evolution of research hot spots and frontier development trends.

Findings

Combined with the visualization results and the content analysis of key references, we identify key literature and examine the evolution of research hotspots and frontier development trends. The bibliometric analysis mainly includes knowledge mapping to identify key themes, co-occurrence and clustering analysis of keywords, cooperation networks in researchers' countries. An overall GP research model is presented and our research suggests future avenues for GP research, such as low carbon, digitalization, servitization and ecosystem perspectives.

Originality/value

Firstly, in terms of time and volume of literature, we have counted the most comprehensive and up-to-date literature in the field of GP research, which is conducive to further expanding and enriching GP research. Secondly, this study clearly describes the theoretical evolution of GP research from bilateral and multilateral to ecosystem perspectives, and constructs a new and comprehensive research framework of “driver-practice-outcome”. Thirdly, based on the bibliometric analysis results, our research suggests future avenues for GP research, such as low-carbon, digitalization, servitization, and ecosystem perspectives, which can contribute to expanding our understanding of GP development.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

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