Finding the path(s) towards profitable e-commerce

Relying on a unique and arguably representative sample of transaction e-commerce companies, this paper takes a closer look at whether and how companies could be profitable on-line. This analysis clearly demonstrates that a non-trivial set of winners are emerging, which combine both strong operational excellence as well as fine-tuned to about 3 generic strategic postures. --E-tailing,Strategic Clusters,Post entry performance

Product market competition with differentiated goods and social welfare in the presence of an industry-wide union

Mainstream locus communis indicates that a more competitive product market leads to higher social welfare levels. Using a Conjectural Variation (CV) model, this research note analyzes the effects on welfare of different degrees of product market competition in a duopoly with differentiated goods. Bargaining between the firms and the industry-wide union occurs under the Efficient Bargaining (EB) model. The work indicates that, with close substitute goods, social welfare is maximized for the inter- mediate levels of market competition, whereas more independent goods lead to the standard result of a high welfare level under competitive markets.info:eu-repo/semantics/publishedVersio

Automatic improvement of apache spark queries using semantics-preserving program reduction

© 2016 ACM. Apache Spark is a popular framework for large-scale data analytics. Unfortunately, Spark's performance can be difficult to optimise, since queries freely expressed in source code are not amenable to traditional optimisation techniques. This article describes Hylas, a tool for automatically optimising Spark queries embedded in source code via the application of semantics-preserving transformations. The transformation method is inspired by functional programming techniques of "deforestation", which eliminate intermediate data structures from a computation. This contrasts with approaches defined entirely within structured query formats such as Spark SQL. Hylas can identify certain computationally expensive operations and ensure that performing them creates no superfluous data structures. This optimisation leads to significant improvements in execution time, with over 10,000 times improvement observed in some cases

SATELLITE IMAGE RECONSTRUCTION FROM AN IRREGULAR SAMPLING

International audienceWe propose a new method to solve a problem of image restoration with many different aspects: reconstruction from irregular samples, deconvolution and denoising. The model we propose is robust to different kind of noises, in particular, impulse and Gaussian noise. We compare our results to the ones obtained in [1] and show that our problem presents some advantages particularly in satellite imaging. At last, we conclude on a discussion about resolution schemes for variational problems' minimization and propose some faster resolution shemes for our problem and the one in [1]

Enterprise social network success: Evidences from a multinational corporation

In a globalized world, where companies operate across different locations and work becomes increasingly complex, collaboration in a diversity of ways is required among employees to perform tasks more effectively. Following a case study methodology that involved six interviews across three different country locations, this research addresses the phenomenon of Enterprise Social Networks (ESN) in a multinational corporation with a focus on the assessment of ESN success. The findings show that the company, while trying to assess the success of Yammer, the freemium social networking service at use, has mainly relied on analytics tools to measure usage through indicators such as the total number of users. However, the extent to which ESN is used does not provide a complete picture of ESN success. Business value from that ESN usage is another dimension to be considered to assess success. Therefore, the study of specific ESN usage scenarios that are perceived to have a trackable impact on business results can be used to assess ESN business value on top of ESN usage to fully understand ESN success.COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013info:eu-repo/semantics/publishedVersio

Towards a novel framework of barriers and drivers for digital transformation in industrial supply chains

© 2019 PICMET. Businesses across all sectors are facing the complexity of an increasingly digital economy. Digital transformation offers vast opportunities to businesses and entire supply chains. While many investments are targeted at the organization level, the supply chain perspective can lead to even greater impacts on business performance. However, as supply chains involve interconnections between multiple actors, comprehensive digitalization initiatives at this level are very complex. Several strategic factors affect decision-making around digital investments. For this reason, a framework that categorizes all these factors is needed in order to help managers build digitalization strategies for their supply chains. In this paper, based on a review of existing literature, we give indications for a framework encompassing barriers to and drivers for digital transformation in the context of industrial supply chains. Our framework preliminarily allocates these factors by using two dimensions. The first one classifies them using several categories: financial, knowledge and skills, regulatory, technological, market, organizational, and cultural. The second dimension classifies determinants at the level on which actions can be made, i.e. market, supply chain, or organization. The framework can support organizations to exploit the opportunities provided by digitalization of supply chains and will help managers understand the complexity involved

Using Big Data to manage safety-related risk in the upstream oil & gas industry: a research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying ‘‘Big Data’’ analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance

Profit sharing as entry deterrence mechanism

In a right-to-manage framework, this paper analyzes the optimal choice of the pay scheme (profit sharing vs. fixed wage) in a unionized duopoly with potential market entry and decentralized bargaining. The paper shows that, depending on the institutional features, both pay systems can arise as equilibria in Nash strategies. Under duopoly with committed bargaining, the fixed wage is the Nash equilibrium; with flexible bargaining, an agreement between the incumbent firm and its union about profit sharing arises as Nash equilibrium, if the union is not too strong. A monopoly with threat of entry reinforces the selection of profit sharing as a deterrent mechanism.info:eu-repo/semantics/publishedVersio