Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

Supplier Development Practices for Sustainability: A Multi‐Stakeholder Perspective

Supplier development for sustainability is a critical element of sustainable supply chain management and requires extensive multi‐stakeholder collaboration. This article establishes a conceptual four‐stage framework to analyse the collaborative mechanisms of supplier development practices, and presents an exploratory, qualitative analysis to identify the major contributors of sustainable supplier development practices, such as NGOs, industrial associations, consulting firms etc. Based on semi‐structured interviews about 63 organizations from different regions and industries, this article identifies three types of contributor: drivers, facilitators and inspectors. Instead of traditional stakeholder engagement processes, these contributors actively collaborate with buying firms and suppliers to design, implement and evaluate sustainable supplier development programs. The article then provides a matrix to describe the supply chain coverage and supplier performance of supplier development practices, given the absence or positive involvement of facilitators and inspectors. We conclude our study by suggesting future research directions as well as discussing managerial implications. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

The Role of Green Collaborative Strategies in Improving Environmental Sustainability in Supply Chains: Insights from a Case Study

This article aims to quantify to what extent collaborative strategies are more effective than internal or organization‐level actions to green supply chains. In this regard, the impact of decisions made at different stages of a supply chain in a product's carbon footprint is quantified. Organizational and product carbon footprints are calculated using the Compound Method Based on Financial Accounts (MC3). The results underline that concentrating reduction efforts in some stages of the supply chain is more effective than implementing individual actions by the participants. Collaboration among the participants is needed to decide what practices are implemented, at what stage they are needed and how they are to be implemented. This article adds to the literature on supply chains and sustainability. Previous research suggests that collaborative strategies have great potential for reducing the carbon footprint of products, while indicating the need for empirical research to support this statement. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Automatic extraction of 1D barcodes from video scans for drone-assisted inventory management in warehousing applications

The widespread use of barcodes has significantly contributed to accurate, efficient and economic inventory management in warehouses and distribution centres. However, its efficiency has always been limited by the primary method of reading barcodes with a handheld laser scanner. Compared with this reading by line-of-sight at close proximity, vision-based barcode reading algorithms can further improve efficiency, particularly if accompanied by automated data collection platforms such as drones. This paper introduces algorithms that are able to automatically extract barcodes from video data, and verifies their feasibility and promise for inventory management in warehousing applications. Three key techniques corresponding to different recognition levels are proposed: For a known barcode region, a Harris corner detector and Hough transform-based algorithm is applied to quickly estimate the angle by which the frame area needs to rotate to orient the bars vertically for information extraction. Then, the idea of exploiting connectivity and geometry property of barcode areas is proposed to directly recognise multiple barcode regions in a single video frame to eliminate reading difficulties resulting from interactive influence of multiple juxtaposed barcodes, and to save computation time by only processing frame areas of interest for valid barcodes. In addition, a histogram difference-based fast extraction strategy is designed to further improve efficiency by reducing duplicate information processing. Finally, the performance of each technique is evaluated by analysing video data from a large logistics warehouse, demonstrating satisfactory performance in inventory management applications.     

Advance selling of new products to strategic consumers on flash sale platforms*

Flash sale (FS) is a new business model that offers discounted products in limited numbers over a short period. In this paper we discuss the impact of strategic consumers on advance selling (AS) of new products on FS platforms. We first study the impact of strategic consumers on competing retailers adopting AS to sell a homogeneous new product. And find that the retailers’ AS profits and inventory quantities decrease with the strategic customers’ valuation and valuation decreasing rate. Then we analyse whether FS can mitigate the impact of strategic customers on retailers adopting AS for new products. We consider a newsvendor model involving only one retailer adopting AS to sell a new product. We derive the results by comparing this model with two counterpart models, namely the classical newsvendor model with no strategic customers and a newsvendor model with strategic customers where the retailer does not use FS under AS.     

Are you really doing good things in your boss's eyes? Interactive effects of employee innovative work behavior and leader–member exchange on supervisory performance ratings

Organizations increasingly depend on employee efforts to innovate. However, the quality of relationships between leaders and employees may affect the recognition that employees receive for their innovative work behaviors. Drawing from a social cognition perspective, we tested a model in which leader–member exchange (LMX) moderates the impact of employee innovative work behavior on supervisory ratings of employee performance. Results from two multisource studies combining self, colleague, and supervisor ratings consistently showed that employees receive more favorable performance ratings by engaging in innovative work behavior when they have high‐quality LMX relationships. Moreover, we found that this interactive relationship was mediated by leader perceptions of innovative employee efforts, providing support for a moderated mediation model. Implications for the literatures on performance appraisal, LMX, and innovation are discussed.     

Pay dispersion among the top management team and outside directors: Its impact on firm risk and firm performance

Two key groups central to improving firm performance are the top management team (TMT) and the board of directors. Executives undertake strategic actions, whereas board members fulfill their resource provision and monitoring roles. Drawing on tournament theory and equity theory, we propose that high pay dispersion among outside directors and the TMT is positively associated with strategic risk, whereas high (low) TMT pay dispersion and low (high) outside director pay dispersion are positively associated with firm performance. Our predictor is the unexplained component of horizontal pay dispersion, or the residual of pay dispersion resulting from regressing pay on observable firm, industry, period, and individual characteristics. Our results highlight the importance of unexplained pay dispersion for TMTs, but not for boards of directors, in improving firm performance.     

Career mentoring in context: A multilevel study on differentiated career mentoring and career mentoring climate

This study explores how supervisor career mentoring contributes to contemporary organizational career development, which strives to foster employees' promotability while strengthening their intention to stay. Specifically, we focus on the implications of career mentoring in team contexts. Applying a multilevel framework, we distinguish between individual‐level differentiated mentoring (i.e., an employee's mentoring perceptions as compared to those of other team members) and group‐level career mentoring climate (i.e., the average perception across all group members). In a workplace setting, we collected data from vocational job starters (N ranged from 230 to 290) and their company supervisors (N ranged from 56 to 68). We find that career mentoring climate positively relates to promotability, more so than differentiated career mentoring. Both career mentoring climate and differentiated career mentoring are positively related to the intention to stay. At the individual level, this relationship is mediated by job satisfaction. We discuss theoretical and practical implications of differentiated and group‐level mentoring.     

The evolution of scale economies in US banking

Continued consolidation of the US banking industry and a general increase in the size of banks have prompted some policymakers to consider policies that discourage banks from getting larger, including explicit caps on bank size. However, limits on the size of banks could entail economic costs if they prevent banks from achieving economies of scale. This paper presents new estimates of returns to scale for US banks based on nonparametric, local‐linear estimation of bank cost, revenue, and profit functions. We report estimates for both 2006 and 2015 to compare returns to scale some 7 years after the financial crisis and 5 years after enactment of the Dodd–Frank Act with returns to scale before the crisis. We find that a high percentage of banks faced increasing returns to scale in cost in both years, including most of the 10 largest bank holding companies. Also, while returns to scale in revenue and profit vary more across banks, we find evidence that the largest four banks operate under increasing returns to scale.     

Multivariate choices and identification of social interactions

This paper considers the identification of social interaction effects in the context of multivariate choices. First, we generalize the theoretical social interaction model to allow individuals to make interdependent choices in different activities. Based on the theoretical model, we propose a simultaneous equation network model and discuss the identification of social interaction effects in the econometric model. We also provide an empirical example to show the empirical salience of this model. Using the Add Health data, we find that a student's academic performance is not only affected by academic performance of his peers but also affected by screen‐related activities of his peers.