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1 – 10 of 189
Article
Publication date: 1 September 2023

Diego Augusto de Jesus Pacheco and Thomas Schougaard

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels…

Abstract

Purpose

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

Design/methodology/approach

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

Findings

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

Practical implications

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

Originality/value

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 10 November 2023

Yong Gui and Lanxin Zhang

Influenced by the constantly changing manufacturing environment, no single dispatching rule (SDR) can consistently obtain better scheduling results than other rules for the…

Abstract

Purpose

Influenced by the constantly changing manufacturing environment, no single dispatching rule (SDR) can consistently obtain better scheduling results than other rules for the dynamic job-shop scheduling problem (DJSP). Although the dynamic SDR selection classifier (DSSC) mined by traditional data-mining-based scheduling method has shown some improvement in comparison to an SDR, the enhancement is not significant since the rule selected by DSSC is still an SDR.

Design/methodology/approach

This paper presents a novel data-mining-based scheduling method for the DJSP with machine failure aiming at minimizing the makespan. Firstly, a scheduling priority relation model (SPRM) is constructed to determine the appropriate priority relation between two operations based on the production system state and the difference between their priority values calculated using multiple SDRs. Subsequently, a training sample acquisition mechanism based on the optimal scheduling schemes is proposed to acquire training samples for the SPRM. Furthermore, feature selection and machine learning are conducted using the genetic algorithm and extreme learning machine to mine the SPRM.

Findings

Results from numerical experiments demonstrate that the SPRM, mined by the proposed method, not only achieves better scheduling results in most manufacturing environments but also maintains a higher level of stability in diverse manufacturing environments than an SDR and the DSSC.

Originality/value

This paper constructs a SPRM and mines it based on data mining technologies to obtain better results than an SDR and the DSSC in various manufacturing environments.

Details

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

Keywords

Article
Publication date: 28 February 2023

Lin-Lin Xie, Yajiao Chen, Sisi Wu, Rui-Dong Chang and Yilong Han

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to…

Abstract

Purpose

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

Design/methodology/approach

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

Findings

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

Originality/value

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 16 November 2023

Felix Preshanth Santhiapillai and R.M. Chandima Ratnayake

The purpose of this study is to investigate the integrated application of business process modeling and notation (BPMN) and value stream mapping (VSM) to improve knowledge work…

Abstract

Purpose

The purpose of this study is to investigate the integrated application of business process modeling and notation (BPMN) and value stream mapping (VSM) to improve knowledge work performance and productivity in police services. In order to explore the application of the hybrid BPMN-VSM approach in police services, this study uses the department of digital crime investigation (DCI) in one Norwegian police district as a case study.

Design/methodology/approach

Service process identification was the next step after selecting an appropriate organizational unit for the case study. BPMN-VSM-based current state mapping, including time and waste analyses, was used to determine cycle and lead time and identify value-adding and nonvalue-adding activities. Subsequently, improvement opportunities were identified, and the current state process was re-designed and constructed through future state mapping.

Findings

The study results indicate a 44.4% and 83.0% reduction in process cycle and lead time, respectively. This promising result suggests that the hybrid BPMN-VSM approach can support the visualization of bottlenecks and possible causes of increased lead times, followed by the systematic identification and proposals of avenues for future improvement and innovation to remedy the discovered inefficiencies in a complex knowledge-work environment.

Research limitations/implications

This study focused on one department in a Norwegian police district. However, the experience gained can support researchers and practitioners in understanding lean implementation through an integrated BPMN and VSM model, offering a unique insight into the ability to investigate complex systems.

Originality/value

Complex knowledge work processes generally characterize police services due to a high number of activities, resources and stakeholder involvement. Implementing lean thinking in this context is significantly challenging, and the literature on this topic is limited. This study addresses the applicability of the hybrid BPMN-VSM approach in police services with an original public sector case study in Norway.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 12 September 2023

Ping Li

The purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health…

Abstract

Purpose

The purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health devices based on the stimulus-organism-response (S-O-R) framework.

Design/methodology/approach

This research conducted an online survey with m-health app users and collected 562 valid responses. A hybrid SEM-ANN approach was employed to evaluate the research model and hypotheses.

Findings

The results show that motivation (M), opportunity (O), and ability (A) affect users’ flow experience and loyalty and further affect their adoption intention of m-health technology. Opportunity plays a more critical role in m-health adoption intention than ability.

Originality/value

This study comprehensively examined the factors that affect users’ deep engagement and m-health adoption from the perspective of MOA. It used the hybrid SEM-ANN method to divide the critical role of motivation, opportunity and ability, providing a new analysis approach for studying information technology (IT) behavior.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 15 November 2023

Hasan Uvet, John Dickens, Jason Anderson, Aaron Glassburner and Christopher A. Boone

This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a…

Abstract

Purpose

This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.

Design/methodology/approach

A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.

Findings

Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.

Research limitations/implications

Implications are limited to the e-commerce B2C domain.

Practical implications

The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.

Originality/value

The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 21 November 2023

Emmanuel Acquah Sawyerr, Michael Bourlakis, Damien Conrad and Carol Wagstaff

This paper explores the nature and operations of the supply chain that serves disadvantaged groups. With the increasing reliance on supplementary food provision through food aid…

Abstract

Purpose

This paper explores the nature and operations of the supply chain that serves disadvantaged groups. With the increasing reliance on supplementary food provision through food aid, the authors seek to emphasise efficiency and sustainability in these supply chains.

Design/methodology/approach

Semi-structured interview data from 32 senior managers and experts from both commercial and food aid supply chains were abductively analysed to develop a relationship-based map of the food chains that serve disadvantaged groups.

Findings

Disadvantaged groups are served by a hybrid food supply chain. It is an interconnected supply chain bringing together the commercial and the food aid supply chains. This chain is unsurprisingly plagued with various challenges, the most critical of which are limited expertise and resources, operational inefficiencies, prohibitive logistics costs and a severe lack of collaboration.

Originality/value

This study identifies the currently limited role of logistics companies in surplus food redistribution and highlights future pathways. Additionally, the authors present useful actionable propositions for managers, practitioners and policymakers.

Details

International Journal of Operations & Production Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 5 February 2024

Swarup Mukherjee, Anupam De and Supriyo Roy

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk…

Abstract

Purpose

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

Design/methodology/approach

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

Findings

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

Research limitations/implications

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

Practical implications

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

Originality/value

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 28 June 2023

Florian Cramer and Christian Fikar

Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for…

Abstract

Purpose

Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).

Design/methodology/approach

A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.

Findings

Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.

Originality/value

Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 29 August 2023

Mendiola Teng-Calleja, Ma. Tonirose de Guzman Mactal and Jaimee Felice Caringal-Go

The purpose of this paper is to explore the various forms of organizational and team-level actions that were perceived to be helpful or not helpful by employees as they navigate…

Abstract

Purpose

The purpose of this paper is to explore the various forms of organizational and team-level actions that were perceived to be helpful or not helpful by employees as they navigate the hybrid work arrangements and how these had an impact on their work behaviors and experiences. This research utilized Bronfenbrenner's ecological systems theory as framework.

Design/methodology/approach

The exploratory study used a qualitative approach in gathering data via online survey from a total of 45 Filipino employees working in a hybrid work arrangement for at least three months. The analysis utilized both inductive and deductive methodologies in examining the data. Inductive thematic analysis was used in coding the data based on the participants' responses, while the deductive approach ensured that the themes are aligned with the research questions and reflect the different systems within Bronfenbrenner's EST (1986).

Findings

Results surfaced helpful organizational (e.g. provision of work tools, financial assistance, supportive policies and engagement and wellness initiatives) and team level actions (i.e. use of technology-based communication tools, open virtual door policy, effective performance management system, employee care practices and team engagement activities). Actions that were perceived as not helpful include inadequate technological infrastructure, poor communication, insufficient training, punitive policies/practices and leadership issues at the organizational level as well as unresponsive colleagues and ineffective implementation of policies/processes at the level of teams. Employees reported being able to build on savings, becoming more productive and having greater work–life balance amid hybrid work. However, they continue to be challenged by blurred boundaries and inability to disconnect from work similar to when work was done remotely and now with sustaining momentum given the shifts on where they do their work.

Practical implications

The findings of this study may guide programs and initiatives of human resource management practitioners and organizational leaders as they support employees in navigating through hybrid work.

Originality/value

The research expands extant knowledge on practices and experiences in hybrid work (Gifford, 2022). It also contributes to studies on human resource management that are nuanced based on where work is performed (Ng and Stanton, 2023) or with emerging work arrangements.

Details

Personnel Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0048-3486

Keywords

1 – 10 of 189