Supplier social engagement, reciprocity of social practices and performance in supply chains

Over the last two decades, social and environmental issues in supply chains have attracted increased scrutiny and debate. Moreover, managers are realizing that irresponsible behavior by their supply chain partners is negatively projected to their firm, with the potential for causing adverse publicity, reputational damage, and costly legal obligations. In my dissertation, I focus on supplier engagement efforts of firms aimed at encouraging suppliers to behave in a socially responsible manner. More formally, the research question addressed in this study is: How can firms engage their overseas suppliers to behave in a socially responsible manner? I propose that supplier engagement is a firm-level capability that reflects an organization’s expertise in deploying resources and routines, usually in combination, to achieve desired social performance as an outcome. I argue that supplier engagement stems from stakeholder engagement capability of a firm and consists of four underlying dimensions: cultural astuteness, operational astuteness, communication capability, and social cognizance. I further argue that supplier social engagement (SSE) capability helps create reciprocity of social practices between a firm and that of its suppliers. Furthermore, SSE capability includes the ability to fashion incentive mechanisms that are more likely to ensure positive social performance. This research followed a two-stage approach. The first stage consisted of semi-structured interviews with industry experts and a systematic review of sustainability reports for a selective sample of firms to develop new measurement scales for the study. Q-sort methodology was employed, augmented by inputs from industry experts, to refine the measurement scales. The second stage of the study consisted of a large-scale survey to validate the study hypotheses. The sampling frame for the second stage comprised of large U.S. firms operating in the manufacturing sector. The data gathered from the large-scale survey was matched to archival performance measures to add validity to the findings of the dissertation. Archival performance data was extracted using the KLD and COMPUSTAT databases

Emerging economy sourcing: Implications of supplier social practices for firm performance

As firms search the world for suppliers that provide the best combination of cost, quality and latest technology, they have been confronted with the challenges of managing the sustainability performance of their global supply chains. Specifically, companies have come under increased scrutiny from various stakeholder groups for the labour and human rights practices of suppliers located in emerging economies. Drawing on the sustainability, supplier relationship management, and stakeholder literature, this research examines the relationship between emerging economy sourcing, the use of purchasing teams, and the impact on enforcement of supplier social practices, and firm financial performance. Using data from a survey and archival sources from a sample of large U.S. firms, findings confirm the mediated role of the use of purchasing teams resulting in better enforcement of supplier social practices and improved firm performance. Findings also provide important implications for supply chain and purchasing executives. While the results of this research demonstrate the performance benefits of sourcing from emerging economies, findings also suggest that organizations should make investments to support capabilities related to enforcement of supplier social practices. Opportunities for future research are also identified

Socially Responsible Practices: An Exploratory Study on Scale Development using Stakeholder Theory

Socially responsible practices of firms have evolved into an important area of research in operations management; however, it remains challenging to identify specific scales that capture multiple dimensions of such social practices. In this exploratory study, we use stakeholder theory to develop new multi‐item measurement scales linked to multiple groups (i.e., internal, supplier, customer, and community stakeholders). Furthermore, we empirically test a higher order multidimensional construct that collectively assesses the socially responsible practices of a firm. Using these stakeholder‐derived constructs as taxons in a cluster analysis, we identify important patterns in the way that multiple groups of stakeholders are engaged. Finally, we demonstrate that the set of social practices are complementary and concentrating on one group can yield spillover effects to other specific stakeholder groups.Canadian Purchasing Research Foundation (CPRF) Social Sciences and Humanities Research Council of Canada (SSHRC

Exploring the implications of supply risk on sustainability performance

Purpose Firms are increasingly being pressured by the public, regulators and customers to ensure that their suppliers behave in a socially and ecologically sound manner. Yet, the complexity and risks embedded in many supply chains makes this challenging, with monitoring practices offering one means to attenuate supply sustainability risk. Drawing on agency theory, the purpose of this paper is to examine the relationship between sustainability and operations risk, supplier sustainability monitoring practices, supply improvement initiatives and firm performance. Design/methodology/approach This research uses data from a survey and archival sources from a sample of large US firms to empirically examine the relationship between sustainability and operations risk, supplier sustainability monitoring practices, supply improvement initiatives and firm performance. Findings Findings indicate that higher levels of perceived sustainability risk is related to greater monitoring of supplier sustainability practices by focal firms. Perceptions of higher operations risk are indirectly related to greater social monitoring through investment in supply improvement initiatives. Monitoring of supplier sustainability practices is also found to have a positive effect on focal firm performance. Practical implications Findings suggest that managers process operations risks and sustainability risks independently. Greater sustainability risk leads to increased sustainability monitoring, while greater operations risk leads to increased investment in supply improvement initiatives, which in turn leads to increased social monitoring. The research also indicates that behavior-oriented approaches, such as monitoring of supplier environmental and social practices, are an effective approach to improving firm sustainability performance. However, due to resource constraints, a challenge for supply chain managers is where and when to invest in behavior-oriented approaches for suppliers. Originality/value This research advances supply risk literature by exploring the effects of supply sustainability risk on the use of monitoring practices to manage supplier environmental and social behavior. Using a combination of survey and archival data to independently assess the implications of sustainability monitoring practices on firm sustainability performance, this study provides a methodology for evaluating the impact of sustainability monitoring practices on the triple bottom line in supply chain management

Pepper leaf curl Lahore virus requires the DNA B component of Tomato leaf curl New Delhi virus to cause leaf curl symptoms

<p>Abstract</p> <p>Background</p> <p>Begomoviruses are whitefly-transmitted geminiviruses with genomes that consist of either two components (known as DNA A and DNA B) or a single component (homologous to the DNA A component of bipartite begomoviruses). Monopartite begomoviruses are often associated with a symptom-modulating DNA satellite (collectively known as betasatellites). Both bipartite and monopartite begomoviruses with associated satellites have previously been identified in chillies showing leaf curl symptoms in Pakistan.</p> <p>Results</p> <p><b>A </b>chilli plant (<it>Capsicum annum</it>) with chilli leaf curl disease symptoms was found to contain a begomovirus, a betasatellite and the DNA B component of <it>Tomato leaf curl New Delhi virus </it>(ToLCNDV). The begomovirus consisted of 2747 nucleotides and had the highest sequence identity (99%) <it>with Pepper leaf curl Lahore virus </it>(PepLCLV-[PK: Lah:04], acc. no. AM404179). <it>Agrobacterium</it>-mediated inoculation of the clone to <it>Nicotiana benthamiana</it>, induced very mild symptoms and low levels of viral DNA, detected in systemically infected leaves by PCR. No symptoms were induced in <it>Nicotiana tabacum </it>or chillies either in the presence or absence of a betasatellite. However, inoculation of PepLCLV with the DNA B component of ToLCNDV induced leaf curl symptoms in <it>N. benthamiana</it>, <it>N. tabacum </it>and chillies and viral DNA accumulated to higher levels in comparison to plants infected with just PepLCLV.</p> <p>Conclusions</p> <p>Based on our previous efforts aimed at understanding of diversity of begomoviruses associated with chillies, we propose that PepLCLV was recently mobilized into chillies upon its interaction with DNA B of ToLCNDV. Interestingly, the putative rep-binding iterons found on PepLCLV (GGGGAC) differ at two base positions from those of ToLCNDV (GGTGTC). This is the first experimental demonstration of the infectivity for a bipartite begomovirus causing chilli leaf curl disease in chillies from Pakistan and suggests that component capture is contributing to the emerging complexity of begomovirus diseases in the region.</p

NEED OF 7S IN SERVICE OPERATION ENVIRONMENT AS COMPARED TO 5S AND 6S

Manufacturing companies distinguish themselves by their operational efficiency and the quality of their products. The 5S and 6S methodologies are commonly used in service operations to enhance efficiency and productivity. Although there are some similarities between these approaches and the 7S technique, there are also notable differences. The 7S technique can be applied in service operations to improve efficiency and productivity by focusing on the spirit element. This study analyzes the significance of the spirit element in the 7S technique and assesses the effectiveness of 5S, 6S, and 7S in service operations. Furthermore, it aims to identify the necessity of the 7S approach in organizations where 5S and 6S are already being used efficiently. The research employs a quantitative methodology and the results indicate that 60% to 79% of the respondents believe that spirit is a crucial aspect of the 7S technique and has positive outcomes. Encouraging a positive spirit can enhance teamwork, motivate and engage employees, and instill a sense of ownership among them. The 7S technique emphasizes an organization's shared values and culture, which can create a positive work environment, encourage employee engagement, improve communication, to lead to better performance

Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers

Analysis of the fairness of machine learning (ML) algorithms recently attracted many researchers' interest. Most ML methods show bias toward protected groups, which limits the applicability of ML models in many applications like crime rate prediction etc. Since the data may have missing values which, if not appropriately handled, are known to further harmfully affect fairness. Many imputation methods are proposed to deal with missing data. However, the effect of missing data imputation on fairness is not studied well. In this paper, we analyze the effect on fairness in the context of graph data (node attributes) imputation using different embedding and neural network methods. Extensive experiments on six datasets demonstrate severe fairness issues in missing data imputation under graph node classification. We also find that the choice of the imputation method affects both fairness and accuracy. Our results provide valuable insights into graph data fairness and how to handle missingness in graphs efficiently. This work also provides directions regarding theoretical studies on fairness in graph data.Comment: Accepted at IEEE International Conference on Big Data (IEEE Big Data

Repair of Accidentally Perforated Labial Wall of a Central Incisor Having Failed Root Treatment -A Case Report

Abstract This is a successfully managed clinical case report of a young lady whose tooth # 11 was root treated in 2010 which reinfected after three years. The root treatment was repeated but was iatrogenically perforated because of the operating dentist&apos;s error. The tooth was therefore opened for surgical correction. During the procedure, it was found that labial wall of the tooth was missing in the mid-root area. The labial wall was built using glass ionomer cement keeping the endodontic file in the canal to avoid obliteration of canal space by glass ionomer. The rebuilt canal was treated with Calcium Hydroxide dressings at an interval of 7 days. In two weeks as the sinus healed, swelling subsided and the canal became effortlessly dryable using just two absorbent points, the canal was obturated with a custom made gutta percha cone, employing glass ionomer as a canal sealer

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

In this paper, we investigate the wireless power transfer and energy-efficiency (EE) optimization problem for nano-centric vehicular networks operating over the terahertz band. The inbody nano-sensors harvest energy from a power station via radio-frequency signal and then use the harvested energy to transmit data to the sink node. By considering the properties of terahertz band (i.e., sensitivity to distance and frequency over the communication path), we adopt the Brownian motion model to develop a time-variant terahertz channel model and to describe the mobility of the nano-sensors. Thus, based on the channel model and energy resources, we further develop a long-term EE optimization problem. The EE optimization is further converted into a series of energy-efficient resource allocation problems over the time slots via equivalent transformation method. The resource allocation problem for each timeslot, which is formulated as a mixed integer nonlinear programming (MINLP), is solved based on the particle swarm optimization (PSO) method. In addition, a dynamic PSO-based EE optimization (DPEEO) algorithm is developed to obtain the sub-optimal solution for the EE optimization problem. By exploiting the special structure of the reformulated problem, an improved DPEEO algorithm, is presented which can handle the problem’s constraints quite well, decreases the research space, and greatly reduces the length of the convergence time. Simulation results validate the theoretical analysis of our system