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Global supply chains enhance value, but are subject to governance problems and encourage evasive practices that deter sustainability, especially in developing countries. This article proposes that the precontractual environment, where parties are interested in trade but have not yet negotiated formal terms, can enable a unique process for building long-term sustainable relations. We argue that precontractual signals based on relation-specific investments, promises of repeated exchange, and reassuring cheap talk can be leveraged in precontract by the power of framing. We show how these framing signals are amplified in precontract because the lack of credible information, minimal time for reflection, and the role of risk-aversion present in supply chain contract negotiations. The result is a process that is uniquely productive for building long-term and valuegenerating contractual relations in supply chains, particularly in skeptical or even hostile negotiating contexts. We then show how framed precontractual signals generate a joint contractual surplus through a supernormal profit known as a relational rent. This rent can be invested to improve sustainable practices, an efficient option in a competitive market due to the second order effects that sustainable practices generate. This novel process we propose thus potentially generates superior returns to other trust measures and encourages focus on precontract as a fertile environment for building sustainable investments.

In this paper, I discuss the dark side of the cascading compliance model predominantly used by multinationals to improve working conditions in global value chains. Further, I discuss the origins of such dark side. Finally, I argue for the move from cascading compliance to a shared responsibility model for the improvement of working conditions in global value chains.

Poor working conditions remain a serious problem in supplier facilities in developing countries. While previous research has explored this from the developed buyers' side, we examine this phenomenon from the perspective of developing countries' suppliers and subcontractors. Utilizing qualitative data from a major knitwear exporting cluster in India and a stakeholder management lens, we develop a framework that shows how the assumptions of conventional, buyer-driven voluntary governance break down in the dilution of buyer power and in the web of factors rooted in suppliers' traditions, beliefs, local demands and resource dependency. We reveal out how success in governing collaborative global supply chains often falls short within the subcontracting stage, where a stakeholder management mindset is elusive to most participants. We suggest that success in governing collaborative global supply chains is dependent on concepts of stakeholder utility and the presence of shared value that is often at odds with the realities of power, information asymmetry and compliance/reward systems inherent in the non-market coordination of global supply chains. Our findings offer important insights for delineating the concepts of value creation from CSR concepts and practices, and for modifying the basic assumptions of conventional supply chain governance.

Global multi-stakeholder initiatives (MSIs) are important instruments that have the potential to improve the social and environmental sustainability of global supply chains. However, they often fail to comprehensively address the needs and interests of various supply-chain participants. While voluntary in nature, MSIs have most often been implemented through coercive approaches, resulting in friction among their participants and in systemic problems with decoupling. Additionally, in those cases in which deliberation was constrained between and amongst participants, collaborative approaches have often failed to materialize. Our framework focuses on two key aspects of these breakdowns: assumptions about the orientation of MSI participants, and the deliberation processes that participants use to engage with each other to create these initiatives and sustain them over time. Drawing from stakeholder and deliberation theories, we revisit the concept of MSIs and show how their deliberative capacity may be enhanced in order to encourage participants to collaborate voluntarily.

PurposeThis paper investigates how organisations are responding to mandatory modern slavery disclosure legislation. Experimentalist governance suggests that organisations faced with disclosure requirements such as those contained in the UK Modern Slavery Act 2015 will compete with one another, and in doing so, improve compliance. The authors seek to understand whether this is the case.Design/methodology/approachThis study is set in the UK public sector. The authors conduct interviews with over 25% of UK universities that are within the scope of the UK Modern Slavery Act 2015 and examine their reporting and disclosure under that legislation.FindingsThe authors find that, contrary to the logic of experimentalist governance, universities' disclosures as reflected in their modern slavery statements are persistently poor on detail, lack variation and have led to little meaningful action to tackle modern slavery. They show that this is due to a herding effect that results in universities responding as a sector rather than independently; a built-in incapacity to effectively manage supply chains; and insufficient attention to the issue at the board level. The authors also identity important boundary conditions of experimentalist governance.Research limitations/implicationsThe generalisability of the authors’ findings is restricted to the public sector.Practical implicationsIn contexts where disclosure under the UK Modern Slavery Act 2015 is not a core offering of the sector, and where competition is limited, there is little incentive to engage in a “race to the top” in terms of disclosure. As such, pro-forma compliance prevails and the effectiveness of disclosure as a tool to drive change in supply chains to safeguard workers is relatively ineffective. Instead, organisations must develop better knowledge of their supply chains and executives and a more critical eye for modern slavery to be combatted effectively. Accountants and their systems and skills can facilitate this development.Originality/valueThis is the first investigation of the organisational processes and activities which underpin disclosures related to modern slavery disclosure legislation. This paper contributes to the accounting and disclosure modern slavery literature by investigating public sector organisations' processes, activities and responses to mandatory reporting legislation on modern slavery.

Despite the expansion of international trade and advancements in global monitoring systems, poor working conditions remain a serious problem in small and medium sized supplier firms in developing countries. To seek to improve working conditions in these supplier firms, we need, at first, a deeper understanding of what factors construct such conditions. Extensive research has been conducted to understand the reasons behind limited improvements in working conditions in developing country supplier facilities. Nevertheless, most of it adopted a global supply chains perspective and failed to take into account the Small and Medium sized Enterprise (SME) perspective. Therefore, rather than adopting one of these perspectives to the exclusion of the other, this thesis seeks to both theoretically and empirically understand the processes associated with the construction of working conditions in SMEs in developing countries that are part of global supply chains. To execute the research intention, knitwear garment exporting SMEs in Tirupur, India, were selected as the research context. Qualitative data were collected mainly via semi-structured interviews with owner-managers, workers, trade union leaders, buying agents, a Non-Governmental Organisation (NGO) leader and a Corporate Social Responsibility (CSR) officer. In addition, supporting data were also collected via non-participant observations, informal conversations and documents for data triangulation. The collected data was then manually analysed using the thematic analysis method. An integrated theoretical framework composed using constructs of institutional theory and organisational sensemaking guided the data analysis. This integrated framework allowed traversing across multiple levels of analysis. Specifically, it aided in understanding the micro processes associated with the construction of working conditions. The empirical findings reveal that the institutional environment in which SMEs are embedded is composed of interconnected, competing, ambiguous and practically impossible to delineate institutional demands providing owner-managers-the primary decision makers-with a platform from which to take part in the construction of working conditions. The findings further reveal that owner-managers in developing countries are resource dependant but not always passive. They interpret and then respond to the institutional demands concerning working conditions in different ways at different points in time; where passive conformance is just one possible response. Through the empirical findings, the thesis contributes to a coherent body of knowledge related to working conditions in SMEs in developing countries that are part of global supply chains. By combining institutional theory with organisational sensemaking in a novel way, the thesis also contributes to the recently growing studies which try to understand how individuals navigate between and respond to competing institutional demands.

Wireless Underground Sensor Networks (WUGSNs) transmit data collected from underground objects such as water substances, oil substances, soil contents, and others. In addition, the underground sensor nodes transmit the data to the surface nodes regarding underground irregularities, earthquake, landslides, military border surveillance, and other issues. The channel difficulties of WUGSNs create uncertain communication barriers. Recent research works have proposed different types of channel assessment techniques and security approaches. Moreover, the existing techniques are inadequate to learn the real-time channel attributes in order to build reactive data transmission models. The proposed system implements Deep Learning-based Multi-Channel Learning and Protection Model (DMCAP) using the optimal set of channel attribute classification techniques. The proposed model uses Multi-Channel Ensemble Model, Ensemble Multi-Layer Perceptron (EMLP) Classifiers, Nonlinear Channel Regression models and Nonlinear Entropy Analysis Model, and Ensemble Nonlinear Support Vector Machine (ENLSVM) for evaluating the channel conditions. Additionally, Variable Generative Adversarial Network (VGAN) engine makes the intrusion detection routines under distributed environment. According to the proposed principles, WUGSN channels are classified based on the characteristics such as underground acoustic channels, underground to surface channels and surface to ground station channels. On the classified channel behaviors, EMLP and ENLSVM are operated to extract the Signal to Noise Interference Ratio (SNIR) and channel entropy distortions of multiple channels. Furthermore, the nonlinear regression model was trained for understanding and predicting the link (channel behaviors). The proposed DMCAP has extreme difficulty finding the differences of impacts due to channel issues and malicious attacks. In this regard, the VGAN-Intrusion Detection System (VGAN-IDS) model was configured in the sensor nodes to monitor the channel instabilities against malicious nodes. Thus, the proposed system deeply analyzes multi-channel attribute qualities to improve throughput in uncertain WUGSN. The testbed was created for classified channel parameters (acoustic and air) with uncertain network parameters; the uncertainties of testbed are considered as link failures, noise distortions, interference, node failures, and number of retransmissions. Consequently, the experimental results show that DMCAP attains 10% to 15% of better performance than existing systems through better throughput, minimum retransmission rate, minimum delay, and minimum energy consumption rate. The existing techniques such as Support Vector Machine (SVM) and Random Forest (RF)-based Classification (SMC), Optimal Energy-Efficient Transmission (OETN), and channel-aware multi-path routing principles using Reinforcement Learning model (CRLR) are identified as suitable for the proposed experiments.

We present SLATE, a sequence labeling approach for extracting tasks from free-form content such as digitally handwritten (or \"inked\") notes on a virtual whiteboard. Our approach allows us to create a single, low-latency model to simultaneously perform sentence segmentation and classification of these sentences into task/non-task sentences. SLATE greatly outperforms a baseline two-model (sentence segmentation followed by classification model) approach, achieving a task F1 score of 84.4%, a sentence segmentation (boundary similarity) score of 88.4% and three times lower latency compared to the baseline. Furthermore, we provide insights into tackling challenges of performing NLP on the inking domain. We release both our code and dataset for this novel task.

Shared autonomy refers to approaches for enabling an autonomous agent to collaborate with a human with the aim of improving human performance. However, besides improving performance, it may often also be beneficial that the agent concurrently accounts for preserving the user's experience or satisfaction of collaboration. In order to address this additional goal, we examine approaches for improving the user experience by constraining the number of interventions by the autonomous agent. We propose two model-free reinforcement learning methods that can account for both hard and soft constraints on the number of interventions. We show that not only does our method outperform the existing baseline, but also eliminates the need to manually tune a black-box hyperparameter for controlling the level of assistance. We also provide an in-depth analysis of intervention scenarios in order to further illuminate system understanding.