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1 – 10 of 34Sanaz Khalaj Rahimi and Donya Rahmani
The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on…
Abstract
Purpose
The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.
Design/methodology/approach
Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.
Findings
Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.
Originality/value
Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.
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Nur Azliani Haniza Che Pak, Suhaiza Ismail and Norhayati Mohd Alwi
The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a…
Abstract
Purpose
The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a stable network.
Design/methodology/approach
Drawing on the actor network theory (ANT), the case of a privatised SWM was studied. Data were collected from all entities involved in the privatisation process of SWM, which include Department A, Corporation X and the private sector concessionaire. Six documents were reviewed, 20 interviews were conducted and two observations were carried out.
Findings
The findings reveal that the control mechanism of SWM is complex, involving the interaction between human and non-human actors. Non-human actors include the key performance indicators (KPIs) and the concessionaire agreement (CA), which are the main control mechanisms towards creating a stable SWM network. Essentially, stability is achieved when the KPIs and CA can influence the activities of both intra- and inter-organisational relationships.
Originality/value
This paper provides a better understanding of the translation process of the MCS that adds to the stability of the network of a privatised SWM from the lens of the ANT.
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Nicola Castellano, Roberto Del Gobbo and Lorenzo Leto
The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on…
Abstract
Purpose
The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.
Design/methodology/approach
The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.
Findings
The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.
Practical implications
The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.
Originality/value
This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.
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Jonathan Mukiza Kansheba, Clavis Nwehfor Fubah and Mutaju Isaack Marobhe
Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors…
Abstract
Purpose
Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.
Design/methodology/approach
The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.
Findings
The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.
Originality/value
This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.
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Temidayo Oluwasola Osunsanmi, Timothy O. Olawumi, Andrew Smith, Suha Jaradat, Clinton Aigbavboa, John Aliu, Ayodeji Oke, Oluwaseyi Ajayi and Opeyemi Oyeyipo
The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present…
Abstract
Purpose
The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.
Design/methodology/approach
This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.
Findings
The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.
Originality/value
Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.
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Sanjeet Singh, Geetika Madaan and Amrinder Singh
Purpose: The availability of resilient energy infrastructure and services is crucial to achieving sustainable development goals. However, defined and trustworthy definitions of…
Abstract
Purpose: The availability of resilient energy infrastructure and services is crucial to achieving sustainable development goals. However, defined and trustworthy definitions of resilience exist solely for engineering and energy systems, particularly in the industrialised world or metropolitan systems. However, no universally accepted definition considers the distinctive characteristics of rural regions in developing economies. To define resilience for rural power systems in developing countries, this chapter synthesises many perspectives on resilience, energy systems, and rural environments.
Methodology: It draws on extensive literature assessments on resilience, particularly concerning energy systems and rural areas, as well as other pre-existing frameworks.
Findings: To account for the unique challenges of electricity supply in rural developing nations, a comprehensive ‘Rural Power System Resilience Framework’ is introduced, including technical, economic, and social resilience.
Social implications: To better understand the elements contributing to the stability of electricity grids in developing nations and rural areas, this resilience framework may be utilised by global markets, system owners and operators, government officials, non-governmental organisations, and communities.
Originality: Through establishing this framework, this study sets the path for developing suitable and ‘effective resilience standards’ tailored for implementation in these rural areas, with the ultimate goal of facilitating the fulfilment of achieving domestic and worldwide sustainability objectives.
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Jeremy Schulz, Laura Robinson and Katia Moles
This chapter explores the development of social science visualizations as cultural objects within art worlds. The research examines artworks as social science visualizations to…
Abstract
This chapter explores the development of social science visualizations as cultural objects within art worlds. The research examines artworks as social science visualizations to show the importance of conducting analysis within distinctive social, institutional, and cultural environments. To make these arguments, the chapter outlines some of the key features of art worlds as they have been analyzed by cultural sociologists and anthropologists. We point out how cultures of reception and institutional intermediaries, such as museums, have historically shaped the construction of artworks, which are never produced or interpreted in a vacuum. The chapter closes with a call to expand both the application of social science visualizations and our understanding of such visualizations as subject to similar art world dynamics. Such visualizations, it is argued, constitute key components of social research practice increasingly oriented toward a digitally connected public hungry for visual interpretations of contemporary social developments.
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Thomas Trabert, Luca Doerr and Claudia Lehmann
The organizational digital transformation (ODT) in companies presents small and medium-sized enterprises (SMEs) – who remain at the beginning of this transformation – with the…
Abstract
Purpose
The organizational digital transformation (ODT) in companies presents small and medium-sized enterprises (SMEs) – who remain at the beginning of this transformation – with the challenge of offering digital services based on sensor technologies. Against this backdrop, the present paper identifies ways SMEs can enable digital servitization through sensor technology and defines the possible scope of the organizational transformation process.
Design/methodology/approach
Around 21 semi-structured interviews were conducted with experts from different hierarchical levels across the German manufacturing SME ecosystem. Using the Gioia methodology, fields of action were identified by focusing on influencing factors and opportunities for developing these digital services to offer them successfully in the future.
Findings
The complexity of existing sensor offerings must be mastered, and employees' (data) understanding of the technology has increased. Knowledge gaps, which mainly relate to technical and organizational capabilities, must be overcome. The potential of sensor technology was considered on an individual, technical and organizational level. To enable the successful implementation of service offerings based on sensor technology, all relevant stakeholders in the ecosystem must network to facilitate shared value creation. This requires standardized technical and procedural adaptations and is an essential prerequisite for data mining.
Originality/value
Based on this study, current problem areas were analyzed, and potentials that create opportunities for offering digital sensor services to manufacturing SMEs were identified. The identified influencing factors form a conceptual framework that supports SMEs' future development of such services in a structured manner.
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Kaisu Laitinen, Mika Luhtala, Maiju Örmä and Kalle Vaismaa
Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency…
Abstract
Purpose
Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.
Design/methodology/approach
Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.
Findings
This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.
Originality/value
This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.
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Mohammad Zarei, Magne Supphellen and Richard P. Bagozzi
The purpose is to use co-citation analysis of servant leadership (SL) research to investigate the evolution of the field, its subfields, gaps and opportunities for future research…
Abstract
Purpose
The purpose is to use co-citation analysis of servant leadership (SL) research to investigate the evolution of the field, its subfields, gaps and opportunities for future research in a systematic manner.
Design/methodology/approach
A document co-citation technique and three clustering algorithms (latent semantic index (LSI), the log-likelihood ratio (LLR) and the mutual information (MI) index) were employed to analyse 24,030 references from 549 articles spanning a period of 50 years.
Findings
Cluster analyses reveal that SL research consists of eight distinct subfields: (1) conceptualisation and measurement of SL; (2) SL and related theories; (3) methodological foundations and empirical expansion of SL research; (4) individual-level cognitive effects of SL and related theories; (5) “Warmth effects” of leadership behaviour; (6) antecedents of effective leadership; (7) SL, marketing, sales management and ethics and (8) SL, job design and work engagement. Important gaps and opportunities for future research are identified.
Research limitations/implications
The analyses do not show a complete picture of research on SL. Interesting works used by subgroups of SL researchers may not have enough citations to be included in the results. Moreover, bibliometric analyses do not explain the impact of books, journals and articles on the practice of SL. The authors welcome future analyses of the most influential sources of SL practice. The authors expect that managerial and practice-oriented books and journals, such as the International Journal of Servant Leadership and the Servant Leadership Theory and Practice, would play a central role in such analyses.
Practical implications
The discussions of the nature of SL, its effects and antecedents are useful to leaders who want to develop a SL style or assist others in developing it. For researchers and doctoral students, the cluster analyses of co-citations give an overview of the subfields of SL research and reveal important knowledge gaps in the literature.
Social implications
SL has several favourable effects on the motivation and psychological well-being of followers. Also, followers tend to adopt a willingness to serve.
Originality/value
Previous research has categorised SL research into three broad categories or phases. The cluster analyses of the co-citations reported here reveal a meaningful structure of eight distinct subfields. Knowledge gaps within the subfields represent novel opportunities for future research on SL. The authors also suggest a new subfield of SL research: pedagogical approaches to the motivation and development of SL skills.
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