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1 – 10 of 11Younès El Manzani, Mostapha El Idrissi and Zakaria Lissaneddine
This study empirically analyzes the direct impacts of soft quality management practices (SQMP) and market orientation ambidexterity (MOA) on product innovation ambidexterity…
Abstract
Purpose
This study empirically analyzes the direct impacts of soft quality management practices (SQMP) and market orientation ambidexterity (MOA) on product innovation ambidexterity (PIA). It also examines the mediating role of MOA in the relationship between SQMP and PIA.
Design/methodology/approach
Following a quantitative research methodology, a well-structured questionnaire is used to collect data from 130 Moroccan certified ISO 9001 firms. The conceptual framework of the study was tested using partial least squares structural equation modeling.
Findings
The results show that SQMP have no significant association with PIA while they positively and significantly impact MOA. The study also revealed that MOA has a positive and significant impact on PIA and fully mediates the relationship between SQMP and PIA.
Research limitations/implications
Due to the conceptualization of MOA and PIA as combined ambidexterity, the results of the study might be different in the case of balanced ambidexterity.
Practical implications
To achieve PIA, managers need to be aware that implementing SQMP, while important, is not enough. They must invest sufficient resources to properly implement these practices to support MOA. Consequently, MOA will lead their organization to PIA by establishing the significant impact of SQMP on PIA.
Originality/value
Regardless of the abundant literature on the relationship between quality management (QM) practices and innovation, this study is among the first to examine the impact of SQMP on PIA. Using MOA as a mediator can give a meaningful answer to the indecisive empirical results of the impact of QM on innovation. Furthermore, this research contributes to the scarce literature on relevant studies conducted in developing countries.
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Effective total quality management (TQM) practices rely on the accurate classification of critical success factors (CSFs). The impact matrix cross-reference multiplication…
Abstract
Purpose
Effective total quality management (TQM) practices rely on the accurate classification of critical success factors (CSFs). The impact matrix cross-reference multiplication technique for classification (MICMAC) or/and fuzzy MICMAC (FMICMAC) can be used to identify key factors in the complex set. However, TQM includes both “hard” and “soft” factors, limiting application of the traditional MICMAC/FMICMAC method.
Design/methodology/approach
Previous literature on TQM was reviewed, CSFs were identified, and factors were sorted into soft and hard categories. The combined fuzzy integration and dual-aspect MICMAC (fuzzy dual-aspect MICMAC approach) was then applied to identify, cluster and prioritize the CSFs of TQM.
Findings
A total of 20 factors (10 soft and 10 hard) were identified and isolated to assess the manufacturing- and service-related TQM practices of the Pearl River Delta Region of China. Seven driver factors and one linkage factor emerged as the key CSFs that managers should prioritize.
Research limitations/implications
A major limitation of this study is the dependency of the results on the definitions of linguistic labels. If the linguistic definitions of TQM CSFs do not closely correspond to the expert opinion data, then the analysis results may be inaccurate. Additionally, although expert opinions are utilized in the proposed method for comprehensive assessments, these opinions may influence the final results due to their inherent subjectivity.
Originality/value
A novel fuzzy dual-aspect MICMAC approach was developed to identify and classify CSFs for optimal TQM practices. This approach allows clustering of CSFs so that decision-makers can prioritize factors according to their dependence and driving powers. Practitioners should concentrate on the CSFs with higher driving powers for successful TQM.
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Manoj Hudnurkar, Suhas Ambekar, Sonali Bhattacharya and Pratima Amol Sheorey
This study attempts to find the structural relationship between Total Quality Management (TQM) and Corporate Sustainability (CS) by analyzing the role of Innovation Capability…
Abstract
Purpose
This study attempts to find the structural relationship between Total Quality Management (TQM) and Corporate Sustainability (CS) by analyzing the role of Innovation Capability (IC).
Design/methodology/approach
The authors conducted the study in the context of manufacturing industries in the Indian Micro Small and Medium Enterprises (MSME) sector. In the process, The authors attempt to throw light on the significance of TQM and IC in bringing out sustainable practices in organizations. The authors used Structural Equation Modeling with AMOS to study the relationship between TQM and CS.
Findings
The authors measured TQM through product control management, process control, vendor quality management and customer relationship improvement. We did find a direct relationship between TQM and CS, along with its three dimensions: environmental sustainability, economic sustainability and social sustainability. TQM was found to be antecedent to IC. IC, measured through product innovation, process innovation and managerial innovation, did not mediate the relation between TQM and CS. However, the link between TQM and social and environmental sustainability partially mediates through IC at the dimension level.
Practical implications
TQM can provide a holistic means of nurturing participation and satisfaction of stakeholders for achieving corporate sustainability and in the process, can create an innovative culture for stimulating a circular social economy.
Originality/value
This study fills the gap in the literature by providing a structural model that explains the relationship between TQM and corporate sustainability and highlights the role of innovation capability in achieving it.
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Mohammed A. Al-Hakimi, Majid M. Goaill, Hamood Mohammed Al-Hattami, Mohsen Ali Murshid, Moad Hamod Saleh and Sami Abdulkareem Mohammed Moghalles
Although understanding how different resources are interconnected within firms is important, there are few studies that have focused on this area. This study aims to explore the…
Abstract
Purpose
Although understanding how different resources are interconnected within firms is important, there are few studies that have focused on this area. This study aims to explore the unique and interactive effects of technical lean practices (TLPs) and human lean practices (TLPs) on the operational performance (OP) of manufacturing SMEs in Yemen, a less developed country (LDC).
Design/methodology/approach
Depending on data collected from 318 manufacturing SMEs in Yemen, the relationships in the proposed model were tested using hierarchical regression analysis via PROCESS Macro V. 3.5 in SPSS.
Findings
The results show that both TLPs and HLPs have unique effects on OP of SMEs. More importantly, both TLPs and HLPs have synergistic effects on OP.
Practical implications
The study would be of interest to Lean practitioners, as the results of this study can be used in firms to put a focus on how TLPs and HLPs have to interact when it comes to the successful implementation of lean manufacturing (LM).
Originality/value
Although research interest in LM is increasing, the interactive effects of TLPs and HLPs remain to be understood. This study provides an initial empirical evidence for performance outcomes from the interaction between TLPs and HLPs of SMEs in LDCs such as Yemen. Most of the previous studies on lean practices have focused on SMEs in developed countries, which may not fully apply to LDCs such as Yemen. This is helpful for SMEs' managers in the context of LDCs to understand how TLPs can further improve OP when interacting with HLPs.
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Emilia Filippi, Loris Gaio and Marco Zamarian
This study aims to analyze how the interplay between hard and soft elements of total quality management (TQM) produces the conditions for sustaining success in the quest for…
Abstract
Purpose
This study aims to analyze how the interplay between hard and soft elements of total quality management (TQM) produces the conditions for sustaining success in the quest for quality.
Design/methodology/approach
A qualitative analysis (Gioia method) was carried out on an original dataset collected through both direct and indirect methods (i.e. archival sources, interviews and observations) to generate a new interpretive framework.
Findings
The interpretative framework identifies four categories of elements: trigger elements create the starting conditions for a quality virtuous cycle; benchmarking tools set the standards of performance; improvement tools enable exploration of the space of possible alternative practices and finally, catalytic forces allow the institutionalization of effective techniques discovered in this search process into new standards.
Research limitations/implications
The findings the authors present in this paper are derived by a single case study, limiting the generalizability of our results in other settings.
Practical implications
This study has three implications: first, the design of trigger elements is critical for the success of any TQM initiative; second, the interplay of improvement and benchmarking tools at several levels should be coherent and third, to exploit the potential of TQM, efforts should be devoted to the dissemination of new effective practices by means of catalyzing elements.
Originality/value
The model provides a more specific understanding of the nature and purpose of the hard and soft elements of TQM and the dynamic interaction between the two classes of elements over time.
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Andreia De Bem Machado, João Rodrigues Dos Santos, António Sacavém and Maria Jose Sousa
Cities are becoming smarter and more optimized because of digital transformation, reducing costs, increasing safety, attracting investment, ensuring sustainability, and increasing…
Abstract
Cities are becoming smarter and more optimized because of digital transformation, reducing costs, increasing safety, attracting investment, ensuring sustainability, and increasing viability. As a result of this optimization, they are becoming smart cities. Smart cities use the Internet of Things’ devices, such as connected sensors, lights, and smart meters, to improve infrastructure and design by gathering and analyzing real-time citizen data. In this research, different conceptions of smart cities and their interconnections with digital transformation are presented. Therefore, the purpose of this chapter is to analyze how digital transformation may help manage smart cities. As a result, a thorough and integrated evaluation of the SCOPUS database will be conducted in order to address the following questions: (1) What are smart cities? (2) What is digital transformation? (3) How does digital transformation help to manage smart cities? The results point out that technologies and digital abundance, which include artificial intelligence, blockchain, and Internet of Things, play a crucial role in managing a controlled and automated infrastructure in smart cities. These favor the development of suitable places to live, work, and have fun, with a better quality of life for everyone.
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Shekwoyemi Gbako, Dimitrios Paraskevadakis, Jun Ren, Jin Wang and Zoran Radmilovic
Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and…
Abstract
Purpose
Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.
Design/methodology/approach
A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.
Findings
The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.
Originality/value
By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.
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This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for…
Abstract
Purpose
This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.
Design/methodology/approach
This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.
Findings
The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.
Originality/value
A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.
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Muneza Kagzi, Sayantan Khanra and Sanjoy Kumar Paul
From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior…
Abstract
Purpose
From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.
Design/methodology/approach
This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.
Findings
ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.
Originality/value
This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.
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Afrooz Moatari-Kazerouni, Dinesh R. Pai, Alejandro E. Chicas and Amin Keramati
The authors propose a blockchain platform for managing clinical trial data to enhance data validity, integrity, trust and transparency in the pharmaceutical research process. The…
Abstract
Purpose
The authors propose a blockchain platform for managing clinical trial data to enhance data validity, integrity, trust and transparency in the pharmaceutical research process. The authors also provide an extensive review of how blockchain technology supports the business processes of clinical trials.
Design/methodology/approach
A systematic literature review was conducted to identify the existing applications of blockchain in pharmaceutical process management. A conceptual design for a blockchain infrastructure to address clinical trial challenges is developed by outlining the entire clinical trial value chain and identifying the coordination and communication among its stakeholders. A stakeholder analysis is conducted to ensure that the clinical trial processes satisfy the requirements and preferences of each stakeholder.
Findings
The proposed blockchain platform offers a promising solution for enhancing integrity, trust and transparency in the clinical trial process. Additionally, blockchain can help streamline communication and collaboration between stakeholders by enabling multiple parties to access and share data in real time, lowering the possibility of delays or errors in data analysis and reporting.
Practical implications
The proposed blockchain platform can benefit patients by empowering them to have better-controlled access to their data and by allowing researchers to maintain adherence to reporting requirements. Additionally, the platform can benefit granting agencies, researchers and decision-makers by ensuring the integrity of clinical trial data and streamlining communication and collaboration between stakeholders.
Originality/value
This study builds on existing blockchain applications in pharmaceutical process management by developing a blockchain framework that can address clinical trial concerns from an integrated perspective.
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