Supplier Strategies and Routines for Capability Development: Implications for Upgrading

\ua9 2018 The Authors. This paper examines the strategies and routines adopted by small and medium-sized suppliers to develop capabilities that enable them to engage in upgrading, despite a precarious relational and institutional context. To this end, we investigate the strategic behaviour of two Bangladeshi garment manufacturers. Both started out as small suppliers for multinational enterprises (MNEs) and have eventually grown into micro-multinationals. The firms are involved in ‘tacit promissory contracting’ with their buyers, a specific form of international outsourcing relationship. The study adopts a multiple case study design that involves interviews with managers/owners of the firms. The analysis yields two key findings. Both firms have devised strategies and taken coherent routines involving actions to develop skills and motivation needed to perform appropriate functional activities (i.e. pre-production, production and post-production) as they embarked on different stages of upgrading. Furthermore, firms have designed routines to internalise the challenges originating from their relationships with their buyers and the institutional environment at the time that had the potential to affect their upgrading goals. The paper contributes to IB studies by highlighting how suppliers, even in a precarious context, can control their own strategies and routines, so as to develop capabilities that allow them to gradually redress the power imbalance between themselves and their buyers

Rana Plaza collapse aftermath: Are CSR compliance and auditing pressures effective?

Purpose: The paper sets out to investigate the intended and unintended consequences of compliance and auditing pressures in the Bangladeshi garment industry. To explore this issue we draw on three medium sized suppliers. The institutional changes that followed the Rana Plaza accident in April 2013 make Bangladesh in general and the garment industry in particular an interesting and suitable research setting for standards compliance. // Design: The study adopts a multiple case study approach. Face-to-face interviews have been conducted with the owners of three Bangladeshi garment manufacturing firms and several workers. Additionally, organisational documents and local newspaper articles had been collected wherever possible. // Findings: The results indicate that the pressure for compliance has led the case companies to prioritise the implementation of measurable standards over the socially grounded needs and priorities of workers. As a consequence certain initiatives instead of adding new social value in fact destroyed previously existing social value. Furthermore, the pressure for compliance created the necessity to find ways to cover the sizable cost of compliance. This prompted firms to pursue process upgrading through technological advancements and increased work pressures on the labour force. These initiatives led to an increased power imbalance and the exclusion of unskilled workers from the job market.// Originality: The paper contributes to the understanding of the human rights implications of compliance and auditing pressures and initiatives. Furthermore, in order to further enrich existing knowledge in the critical accounting literature, the study draws on insights from the global value chains (GVC) and international business (IB) literatures

Supplier strategies to compensate for knowledge asymmetries in buyer-supplier relationships: Implications for economic upgrading

Knowledge acquisition, Knowledge sources, Economic upgrading, Buyer-supplier relationship, Outsourcin

Negotiating the ethical terrain in global value chains on the road towards the SDGs

This paper employs a pattern matching approach to explore the tensions arising from differences in the ethical dispositions of multinational enterprise (MNE) buyers and their suppliers within the Bangladeshi apparel manufacturing sector. It examines how varying ethical principles shape the development, implementation, and outcomes of corporate social responsibility (CSR) and labor standards. Our analysis resulted in the identification of four scenarios: legitimacy with friction, mitigated forced alignment, collaborative enhancement, and principled resistance. However, the scenario, principled resistance, is purely conceptual, as none of our empirical cases aligned with this category. We extend work highlighting the importance of ethical foundations for strategic decision making. This study advances the understanding of global value chain governance, particularly regarding MNEs’ contribution to the socially oriented Sustainable Development Goals. Our findings suggest that, out of the four scenarios, the combination of virtue ethics and consequentialist principles is most likely to facilitate a just transition to a more desirable state in contexts characterized by development challenges and institutional voids

Resilience, political ecology, and well-being: An interdisciplinary approach to analysing social-ecological change in coastal Bangladesh

The commodification of peasant livelihoods through export-oriented aquaculture has brought about significant social-ecological changes in low-lying coastal areas in many parts of Asia. A better understanding of the underlying drivers and distributional effects of these changes requires integration of social and ecological approaches that often have different epistemological origins. Resilience thinking has gained increased traction in social-ecological systems research because it provides a dynamic analysis of the cross-scalar interactions between multiple conditions and processes. However, the system-oriented perspective inherent in resilience thinking fails to acknowledge the heterogeneous values, interests, and power of social actors and their roles in navigating social-ecological change. Incorporation of political ecology and well-being perspectives can provide an actor-oriented analysis of the trade-offs associated with change and help to determine which state is desirable for whom. However, empirical demonstrations of such interdisciplinary approaches remain scarce. Here, we explore the combined application of resilience, political ecology, and well-being in investigating the root causes of social-ecological change and identifying the winners and losers of system transformation through empirical analysis of the differential changes in farming systems in two villages in coastal Bangladesh. Using the adaptive cycle as a structuring model, we examine the evolution of the shrimp aquaculture system over the past few decades, particularly looking at the power dynamics between households of different wealth classes. We found that although asymmetric land ownership and political ties enabled the wealthier households to reach their desired farming system in one village, social resilience achieved through memory, leadership, and crisis empowered poorer households to exercise their agency in another village. Material dimensions such as improved living standards, food security, and cash incomes were evidently important; however, freedom to pursue desired livelihood activities, better environmental quality, mental peace, and cultural identities had significant implications for relational and subjective well-being

A social-ecological analysis of drinking water risks in coastal Bangladesh

Groundwater resources in deltaic regions are vulnerable to contamination by saline seawater, posing significant crisis for drinking water. Current policy and practice of building water supply infrastructure, without adequate hydrogeological analysis and institutional coordination are failing to provide basic drinking water services for millions of poor people in such difficult hydrogeological contexts. We apply a social-ecological systems approach to examine interdisciplinary data from hydrogeological mapping, a water infrastructure audit, 2103 household surveys, focus group discussions and interviews to evaluate the risks to drinking water security in one of 139 polders in coastal Bangladesh. We find that increasing access through public tubewells is common but insufficient to reduce drinking water risks. In response, there has been a four-fold growth in private investments in shallow tubewells with new technologies and entrepreneurial models to mitigate groundwater salinity. Despite these interventions, poor households in water-stressed environments face significant trade-offs in drinking water quality, accessibility and affordability. We argue that institutional coordination and hydrogeological monitoring at a systems level is necessary to mitigate socio-ecological risks for more equitable and efficient outcomes

Role of metaheuristic algorithms in healthcare: a comprehensive investigation across clinical diagnosis, medical imaging, operations management, and public health

Metaheuristic algorithms have emerged in recent years as effective computational tools for addressing complex optimization problems in many areas, including healthcare. These algorithms can efficiently search through large solution spaces and locate optimal or near-optimal responses to complex issues. Although metaheuristic algorithms are crucial, previous review studies have not thoroughly investigated their applications in key healthcare areas such as clinical diagnosis and monitoring, medical imaging and processing, healthcare operations and management, as well as public health and emergency response. Numerous studies also failed to highlight the common challenges faced by metaheuristics in these areas. This review thus offers a comprehensive understanding of metaheuristic algorithms in these domains, along with their challenges and future development. It focuses on specific challenges associated with data quality and quantity, privacy and security, the complexity of high-dimensional spaces, and interpretability. We also investigate the capacity of metaheuristics to tackle and mitigate these challenges efficiently. Metaheuristic algorithms have significantly contributed to clinical decision-making by optimizing treatment plans and resource allocation and improving patient outcomes, as demonstrated in the literature. Nevertheless, the improper utilization of metaheuristic algorithms may give rise to various complications within medicine and healthcare despite their numerous benefits. Primary concerns comprise the complexity of the algorithms employed, the challenge in understanding the outcomes, and ethical considerations concerning data confidentiality and the well-being of patients. Advanced metaheuristic algorithms can optimize the scheduling of maintenance for medical equipment, minimizing operational downtime and ensuring continuous access to critical resources

Enhancement of traffic forecasting through graph neural network-based information fusion techniques

To improve forecasting accuracy and capture complex interactions within transportation networks, information fusion approaches are crucial for traffic predictions based on graph neural networks (GNNs). GNNs offer a potentially effective framework for capturing complex patterns and interactions among diverse elements, such as road segments and crossings, by considering both temporal and geographical dependencies. Although GNN-based traffic forecasting has recently been investigated in many studies, there is a need for comprehensive reviews that examine information fusion approaches for GNN-based traffic predictions, including an analysis of their benefits and challenges. This study addresses this knowledge gap and offers future insights into the potential advancements and developing fields of research in GNN-based fusion techniques, as well as their implications in urban planning and smart cities. Existing research demonstrates that the accuracy of traffic forecasting is substantially enhanced by information fusion techniques based on GNNs in comparison to more conventional approaches. By integrating information fusion methods with GNNs, the model is capable of capturing complex temporal and spatial relationships between various locations in a traffic network. Multi-source data integration benefits traffic forecasting models, including social events, weather conditions, real-time traffic sensor data, and historical traffic patterns. In addition, combining GNNs with other artificial intelligence (AI) methods like evolutionary algorithms or reinforcement learning could be an efficient strategy. With the potential to combine the best features of several methods, hybrid models could improve overall performance and flexibility in challenging traffic situations

Genome wide in silico SNP-tumor association analysis

BACKGROUND: Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue. METHODS: An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106). RESULTS: A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation CONCLUSIONS: This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer