Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain

Multi-demand supply chain triads and the role of Third-Party Logistics Providers

Purpose

Third-party logistics providers (3PLs) have significantly evolved during the last decades, yet their role within a supply chain triad has been overlooked; this study examines empirically the 3PLs' role using four established theories: resource-based view, social capital perspective, agency theory and transaction cost economics.

Design/methodology/approach

This study examines the role of 3PLs in four supply chain triads, using the case study approach. Sources of evidence include interviews and secondary data.

Findings

The 3PL had different roles in multi-demand triads as service developer, customer adaptor and customer developer. The 3PL, by offering advanced services, became a service developer. The 3PL as a customer adaptor offered customised services and gain the client's trust. As a customer developer, the 3PL acted on behalf of its client in expanding its operations and meeting competitive needs.

Research limitations/implications

The results of the case study methodology can only be generalised to similar types of 3PL. Supply chain triads are an emerging research field; theories like the resource-based view and transaction cost economics are established in the dyadic context and require further elaboration when applied in triadic contexts.

Practical implications

The findings provide practical insights into the role that 3PL can play in supply chain triads, how they can upgrade their role by long-range planning and extending their services to create supply chain efficiency.

Social implications

Understanding the 3PL's role in triads can improve how companies and economies respond to crises like the recent pandemic outbreak.

Originality/value

It uncovers three different 3PL roles in supply chain triads by using four established theories.

A systematic literature review on the use of big data analytics in humanitarian and disaster operations

At the start of this review, 168 million individuals required humanitarian assistance, at the conclusion of the research, the number had risen to 235 million. Humanitarian aid is critical not just for dealing with a pandemic that occurs once every century, but more for assisting amid civil conflicts, surging natural disasters, as well as other kinds of emergencies. Technology's dependability to support humanitarian and disaster operations has never been more pertinent and significant than it is right now. The ever-increasing volume of data, as well as innovations in the field of data analytics, present an incentive for the humanitarian sector. Given that the interaction between big data and humanitarian and disaster operations is crucial in the coming days, this systematic literature review offers a comprehensive overview of big data analytics in a humanitarian and disaster setting. In addition to presenting the descriptive aspects of the literature reviewed, the results explain review of existent reviews, the current state of research by disaster categories, disaster phases, disaster locations, and the big data sources used. A framework is also created to understand why researchers employ various big data sources in different crisis situations. The study, in particular, uncovered a considerable research disparity in the disaster group, disaster phase, and disaster regions, emphasising how the focus is on reactionary interventions rather than preventative approaches. These measures will merely compound the crisis, and so is the reality in many COVID-19-affected countries. Implications for practice and policy-making are also discussed.

Peace engineering and compassionate operations: a framework for leveraging social good

Purpose

Peace engineering and compassionate operations can unlock the potential of emerging technologies for social good. This work aims to investigate the integration of peace engineering and compassionate operations by proposing an integrative framework and identifying the main drivers regarding social good, considering the Sustainable Development Goals (SDGs) landscape.

Design/methodology/approach

The authors used a two-stage methodology by employing a narrative literature review in the first stage to identify the relationships and drivers and propose an original framework. In the second stage, the authors utilized an expert panel to validate the framework’s drivers.

Findings

The authors identified five main categories related to peace engineering and compassionate operations, which were then used to support the categorization of the drivers. In the second stage, the authors validated the drivers with a panel of academicians and experienced industry practitioners.

Practical implications

The proposed framework can provide insightful directions for practitioners and governments to develop strategies and projects in different contexts, including humanitarian logistics, climate change crises, supply chain disruptions, etc.

Originality/value

This work makes unique contributions by reinvigorating an amalgamation of the peace engineering and compassionate operations arenas and their integration with the SDGs to enable enhanced social good, supported by cutting-edge technologies. Thus, this framework’s contributions encompass essential theoretical, managerial, and social implications.

Meta-analysis of Supply Chain Disruption Research

The purpose of this chapter is to provide insights into literature on supply chain disruption research with a specific focus on future research opportunities. A structured meta-literature review approach covering 93 literature reviews was chosen. Quantitative and qualitative content analysis and bibliographic network analysis are applied to highlight trends and research gaps. The meta-analysis shows the current and past academic discourse on supply chain disruptions. Furthermore, this research establishes a research framework and highlights future research opportunities. The research points to research topics that should be addressed in the future. The paper provides a holistic understanding of literature on supply chain disruptions in the commercial and humanitarian context.

The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review

The role of digital technologies (DTs) in humanitarian supply chains (HSC) has become an increasingly researched topic in the operations literature. While numerous publications have dealt with this convergence, most studies have focused on examining the implementation of individual DTs within the HSC context, leaving relevant literature, to date, dispersed and fragmented. This study, through a systematic literature review of 110 articles on HSC published between 2015 and 2020, provides a unified overview of the current state-of-the-art DTs adopted in HSC operations. The literature review findings substantiate the growing significance of DTs within HSC, identifying their main objectives and application domains, as well as their deployment with respect to the different HSC phases (i.e., Mitigation, Preparedness, Response, and Recovery). Furthermore, the findings also offer insight into how participant organizations might configure a technological portfolio aimed at overcoming operational difficulties in HSC endeavours. This work is novel as it differs from the existing traditional perspective on the role of individual technologies on HSC research by reviewing multiple DTs within the HSC domain.

Assessing the role of industry 4.0 for enhancing swift trust and coordination in humanitarian supply chain

Unpredictable natural and man-made disasters highlight importance of humanitarian supply chain (HSC) to serve people and affected areas. The main challenges of applying effective relief operations are creating "swift trust" and "coordination" between aid organizations. Implementation of Industry 4.0 facilitates coordination and swift trust within HSC performance. The study intends to assess the readiness status of swift trust and coordination between stakeholders as well as to recommend the most suitable Industry 4.0 tools for improving relief operations. Firstly, a comprehensive set of critical success factors for implementing Industry 4.0 tools are introduced. The factors are categorized into limited groups using Exploratory Factor Analysis. In the next step, hierarchy fuzzy expert system is designed for assessing the readiness status of swift trust and coordination as well as to suggest the most suitable Industry 4.0 tool for enhancing HSC performance within given case study. The framework was applied for three aid organizations to address the pandemic disease in Iran. The outcome denotes that the organization has the highest readiness in logistic and transparency while information quality received the lowest readiness value. In addition to that, the organization should invest on the development of Industry 4.0 enablers including "Internet of Things and Big Data Analytics". The study extends organizational information process theory within HSC for reaching competitive advantage by information processing. The study suggests theoretical and practical implications by introducing a comprehensive set of critical success factors for implementation of Industry 4.0 and providing practical advice for enhancing HSC performance.

Assessing the role of industry 4.0 for enhancing swift trust and coordination in humanitarian supply chain

Unpredictable natural and man-made disasters highlight importance of humanitarian supply chain (HSC) to serve people and affected areas. The main challenges of applying effective relief operations are creating "swift trust" and "coordination" between aid organizations. Implementation of Industry 4.0 facilitates coordination and swift trust within HSC performance. The study intends to assess the readiness status of swift trust and coordination between stakeholders as well as to recommend the most suitable Industry 4.0 tools for improving relief operations. Firstly, a comprehensive set of critical success factors for implementing Industry 4.0 tools are introduced. The factors are categorized into limited groups using Exploratory Factor Analysis. In the next step, hierarchy fuzzy expert system is designed for assessing the readiness status of swift trust and coordination as well as to suggest the most suitable Industry 4.0 tool for enhancing HSC performance within given case study. The framework was applied for three aid organizations to address the pandemic disease in Iran. The outcome denotes that the organization has the highest readiness in logistic and transparency while information quality received the lowest readiness value. In addition to that, the organization should invest on the development of Industry 4.0 enablers including "Internet of Things and Big Data Analytics". The study extends organizational information process theory within HSC for reaching competitive advantage by information processing. The study suggests theoretical and practical implications by introducing a comprehensive set of critical success factors for implementation of Industry 4.0 and providing practical advice for enhancing HSC performance.

Assessing the role of industry 4.0 for enhancing swift trust and coordination in humanitarian supply chain

Unpredictable natural and man-made disasters highlight importance of humanitarian supply chain (HSC) to serve people and affected areas. The main challenges of applying effective relief operations are creating "swift trust" and "coordination" between aid organizations. Implementation of Industry 4.0 facilitates coordination and swift trust within HSC performance. The study intends to assess the readiness status of swift trust and coordination between stakeholders as well as to recommend the most suitable Industry 4.0 tools for improving relief operations. Firstly, a comprehensive set of critical success factors for implementing Industry 4.0 tools are introduced. The factors are categorized into limited groups using Exploratory Factor Analysis. In the next step, hierarchy fuzzy expert system is designed for assessing the readiness status of swift trust and coordination as well as to suggest the most suitable Industry 4.0 tool for enhancing HSC performance within given case study. The framework was applied for three aid organizations to address the pandemic disease in Iran. The outcome denotes that the organization has the highest readiness in logistic and transparency while information quality received the lowest readiness value. In addition to that, the organization should invest on the development of Industry 4.0 enablers including "Internet of Things and Big Data Analytics". The study extends organizational information process theory within HSC for reaching competitive advantage by information processing. The study suggests theoretical and practical implications by introducing a comprehensive set of critical success factors for implementation of Industry 4.0 and providing practical advice for enhancing HSC performance.

Business Intelligence and Business Value in Organisations: A Systematic Literature Review

Organisations must derive adequate business value (BV) from Business Intelligence (BI) adoption to retain their profitability and long-term sustainability. Yet, the nuances that define the realisation of BV from BI are still not understood by many organisations that have adopted BI. This paper aims to foster a deeper understanding of the relationship between Business Intelligence (BI) and business value (BV) by focusing on the theories that have been used, the critical factors of BV derivation, the inhibitors of BV, and the different forms of BV. To do this, a systematic literature review (SLR) methodology was adopted. Articles were retrieved from three scholarly databases, namely Google Scholar, Scopus, and Science Direct, based on relevant search strings. Inclusion and exclusion criteria were applied to select ninety-three (93) papers as the primary studies. We found that the most used theoretical frameworks in studies on BI and BV are the Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), Technology-Organisation-Environment (TOE), and Contingency Theory (CON). The most acknowledged critical factors of BV are skilled human capital, BI Infrastructure, data quality, BI application and usage/data culture, BI alignment with organisational goals, and top management support. The most acclaimed inhibitors of BV are data quality and handling, data security and protection, lack of BI Infrastructure, and lack of skilled human resource capital, while customer intelligence is the most acknowledged form of BV. So far, many theories that are relevant to BI and BV, critical factors, inhibitors, and forms of BV were marginally mentioned in the literature, requiring more investigations. The study reveals opportunities for future research that can be explored to gain a deeper understanding of the issues of BV derivation from BI. It also offers useful insights for adopters of BI, BI researchers, and BI practitioners.

Industry 4.0, Disaster Risk Management and Infrastructure Resilience: A Systematic Review and Bibliometric Analysis

The fourth industrial era, known as ‘Industry 4.0’ (I4.0), aided and abetted by the digital revolution, has attracted increasing attention among scholars and practitioners in the last decade. The adoption of I4.0 principles in Disaster Risk Management (DRM) research and associated industry practices is particularly notable, although its origins, impacts and potential are not well understood. In response to this knowledge gap, this paper conducts a systematic literature review and bibliometric analysis of the application and contribution of I4.0 in DRM. The systematic literature review identified 144 relevant articles and then employed descriptive and content analysis of a focused set of 70 articles published between 2011 and 2021. The results of this review trace the growing trend for adoption of I4.0 tools and techniques in disaster management, and in parallel their influence in resilient infrastructure and digital construction fields. The results are used to identify six dominant clusters of research activity: big data analytics, Internet of Things, prefabrication and modularization, robotics and cyber-physical systems. The research in each cluster is then mapped to the priorities of the Sendai framework for DRR, highlighting the ways it can support this international agenda. Finally, this paper identifies gaps within the literature and discusses possible future research directions for the combination of I4.0 and DRM.

Performance measurement and NPOs' effectiveness: does internal stakeholders' trust matter? Evidence from Palestine

Purpose

This study proposes a model of the effect of financial and non-financial performance measures on nonprofit organizations’ (NPOs’) effectiveness where internal stakeholders' trust play an intervening role in the aforementioned relationships.

Design/methodology/approach

Data were collected from 218 employees working at the largest Palestinian NPOs. The perceptions of these employees were used to measure the variables, and structural equation modeling was used to examine the hypotheses.

Findings

Results suggest that the use of financial and non-financial performance measures was positively related to NPOs' effectiveness. Internal stakeholders' trust showed a significant mediating effect between the use of performance measures and NPOs' effectiveness.

Practical implications

This study may be of value for NPOs' managers due to the positive effects performance measurement (PM) can have on NPO effectiveness. Managers and boards should seek to enhance their internal stakeholders' trust to achieve higher levels of effectiveness.

Originality/value

This study has three main contributions. First, it is one of the very few papers which empirically examines the links between PM and NPOs' effectiveness, rather than providing conceptual lens. Second, the paper investigates the role of stakeholders' trust as a mediating mechanism in the proposed model, a topic that has been neglected by NPOs governance researchers. Finally, the study uses data from the Palestinian context, contributing to the PM literature by providing evidence on the relationship between performance measures and NPOs' effectiveness from a non-Western context.

Modelling performance measurement barriers of humanitarian supply chain

Purpose

Humanitarian supply chain (HSC) has been constantly challenged with multiple issues due to the complex dynamics of the disaster. These issues are inevitable and interrelated. The issues produce undesirable cascading effects that make performance measurement complicated. This paper aims to identify and model the critical barriers in the HSC.

Design/methodology/approach

The study identifies 17 barriers through the relevant literature and interviews with the stakeholders related to humanitarian organization (HO) in the developing economy. The barriers have been identified from strategic, technological, organizational, economic and operational point of view. Further, the barriers were ranked based on the degree of influence using the grey analytic network process (ANP) approach. The interrelationship among the influential barriers is established through modified total interpretive structural modelling (mTISM). To analyse and demonstrate the iterative consensus among the stakeholders, kappa statistics was adopted.

Findings

The barriers have been ranked to determine their extent of influence and modelled to reveal the interrelationship among them. The issues concerned with skills of personnel are the most influential barrier. Other three critical barriers identified are: chaotic operative environment, conflicting objectives of HO and lack of funding for information technology (IT) infrastructure. Appropriate funds need to be allocated towards IT infrastructure and personnel training.

Originality/value

Both quantitative and qualitative performance measurement frameworks had been proposed earlier for HSC. However, limited literature addresses the implementation issues with the available frameworks. This study advances the knowledge on performance measurement barriers of HSC and develops a functional description to identify the critical role of performance measurement in HOs. The study proposes a new version of the interpretive structure modelling, using mTISM technique, to determine the contextual interactions between various HSC performance measurement barriers.