A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling

AbstractWe propose a min-flow algorithm for detecting Minimal Critical Sets (MCS) in Resource Constrained Project Scheduling Problems (RCPSP). The MCS detection is a fundamental step in the Precedence Constraint Posting method (PCP), one of the most successful approaches for the RCPSP. The proposed approach is considerably simpler compared to existing flow based MCS detection procedures and has better scalability compared to enumeration- and envelope-based ones, while still providing good quality Critical Sets. The method is suitable for problem variants with generalized precedence relations or uncertain/variable durations

Definitions and Measures of ICT Impact on Growth: What is Really at Stake?

Many innovations have been introduced in national accounts in order to better gauge the information and communication technologies (ICT) diffusion impact: new ICT definitions; recognition of business and government software expenditures as fixed investment; hedonic price index. Nevertheless, there still does not exist any clear consensus about the magnitude of the ICT impact on growth. Our aim is to propose some explanations of this relative failure and also show that the debate should not be exclusively centered on quantitative methods. To this end, we take a close look at the two main questions concerning the debate surrounding the measure of the ICT impact: 1) Are there any substantial total factor productivity (TFP) gains generated by ICT diffusion or is it only a classic story of capital deepening increase ? 2) If there are indeed TFP gains, are they limited to ICT producers, as Robert J.Gordon claims, or is there any diffusion to ICT users ? The answer to the first question is really important only if it determines the length and the extent of an eventual growth cycle impulsed by ICT. The possibility that productivity gains mainly due to capital deepening generate strong and durable growth has been theoritically demonstrated by Greenwood and Jovanovic (1998), thanks to a vintage capital model. We precise the conditions under which this result can be obtained and discuss their empirical relevance. According to this approach, the true debate concerns the durability of the present technological shock, instead of its capacity to generate an autonomous technical progress. The answer to the second question is crucial because it could guide industrial policy choices. If TFP gains are limited to ICT producers, should a country always be an ICT producer, or will it anyway grow at a strong pace thanks to the fall of ICT prices ? The relevance of this economic debate is unfortunately poised by the shortcomings of available statistical tools. On one hand, the distinction between ICT users and producers is purely discretionary. On the other hand, TFP measure is completely distorted by the method used to evaluate the value of capital (cost-based prices against adjusted-quality prices). That is why we argue that the international diffusion of growth gains due to ICT essentially depends on the capacity of ICT producers' countries to stay in a rent keeping situation. The text is divided into two parts. The first one first makes a quick assessment of the adaptation of american national accounts to the " new economy ", and then underlines the limits of these changes. The second one shows that the economic debate on the importance of TFP gains acceleration and where they occur, although more complex because of these limits, can quite ignore them thanks to the implications of some endogeneous growth and international trade models.ICT; multifactor productivity; national accounts; hedonic prices

Understanding Digital Technology’s Evolution and the Path of Measured Productivity Growth: Present and Future in the Mirror of the Past

Three styles of explanation have been advanced by economists seeking to account for the so-called 'productivity paradox'. The coincidence of a persisting slowdown in the growth of measured total factor productivity (TFP) in the US, since the mid-1970's, with the wave of information technology (It) innovations, is said by some to be an illusion due to the mismeasurement of real output growth; by others to expose the mistaken expectations about the benefits of computerization; and by still others to reflect the amount of time, and the volume of intangible investments in 'learning', and the time required for ancillary innovations that allow the new digital technologies to be applied in ways that are reflected in measured productivity growth. This paper shows that rather than viewing these as competing hypotheses, the dynamics of the transition to a new technological and economic regime based upon a general purpose technology (GPT) should be understood to be likely to give rise to all three 'effects.' It more fully articulates and supports this thesis, which was first advanced in the 'computer and dynamo' papers by David (1990, 1991). The relevance of that historical experience is re-asserted and supported by further evidence rebutting skeptics who have argued that the diffusion of electrification and computerization have little in common. New evidence is produced about the links between IT use, mass customization, and the upward bias of output price deflators arising from the method used to 'chain in' new products prices. The measurement bias due to the exclusion of intangible investments from the scope of the official national product accounts also is examined. Further, it is argued that the development of the general-purpose PC delayed the re-organization of businesses along lines that would have more directly raised task productivity, even though the technologies yielded positive 'revenue productivity' gains for large companies. The paper concludes by indicating the emerging technical and organizational developments that are likely to deliver a sustained surge of measured TFP growth during the decades that lie immediately ahead.

Stream Processing Systems Benchmark: StreamBench

Batch processing technologies (Such as MapReduce, Hive, Pig) have matured and been widely used in the industry. These systems solved the issue processing big volumes of data successfully. However, first big amount of data need to be collected and stored in a database or file system. That is very time-consuming. Then it takes time to finish batch processing analysis jobs before get any results. While there are many cases that need analysed results from unbounded sequence of data in seconds or sub-seconds. To satisfy the increasing demand of processing such streaming data, several streaming processing systems are implemented and widely adopted, such as Apache Storm, Apache Spark, IBM InfoSphere Streams, and Apache Flink. They all support online stream processing, high scalability, and tasks monitoring. While how to evaluate stream processing systems before choosing one in production development is an open question. In this thesis, we introduce StreamBench, a benchmark framework to facilitate performance comparisons of stream processing systems. A common API component and a core set of workloads are defined. We implement the common API and run benchmarks for three widely used open source stream processing systems: Apache Storm, Flink, and Spark Streaming. A key feature of the StreamBench framework is that it is extensible -- it supports easy definition of new workloads, in addition to making it easy to benchmark new stream processing systems

Value co-creation intention, practices and experience in self-service technologies

The 21st century is known as the experience economy where the prime aim of businesses is to provide superior customer experiences, mainly through actively seeking mutually beneficial interactions with customers which is often labelled as ‘value co-creation’. Co- creation indicates a collaborative perspective of value creation and changes the roles of the organisation into ‘value facilitators’, and customers’ from passive to active as ‘co- creators’. Extant research suggests that businesses which acknowledge this new collective practice achieve greater organisational performance. However, success is not always guaranteed in co-creation; it is an ever-present possibility that a sub optimal implementation may result in value ‘co-destruction’ which causes to diminish wellbeing of the participants.Advances in technologies have presented many opportunities for both organisations and customers to access a multitude of technological interfaces, prompting organisations to explore how self-service technologies (SSTs) can be effectively used in value creation. Despite these advances in SSTs, scholarly work in value co-creation context is largely limited to exploring interpersonal interactions in traditional physical interfaces. To the best of the researcher’s understanding, no studies examine how customers co-create value (value co-creation practices) in SSTs. An inquiry as to whether customers would like to co-create value in SSTs (co-creation intention), what customers do while co-creating value (value co-creation practices) and how they experience their collaboration (co- creation experience) in SST is therefore important.Mixed methodology is adopted, based on the sequential exploratory strategy, where a qualitative study is followed by a quantitative study, such that the findings of the qualitative study are instrumental in designing the quantitative study. The ‘practice theory’ is used as the theoretical foundation in understanding customer value co-creation practices and ‘total customer experience’ is used in understanding customer co-creation experiences.The qualitative study explores eight determinants of co-creation intention and sixteen customer value co-creation practices which are re-classified into five groups of practices (5Cs): co-learning, co-producing, co-operating, connecting and correcting. There is also evidence on the duality of these practices resulting in co-creation and co-destruction, and interconnectivity among practices.Following a confirmatory approach in the quantitative phase, a high level of customer value co-creation intention in SSTs is recognised. ‘Technology know-how’ is found to be the strongest predictor of co-creation intention while performance, information richness and situational factors show significant direct effects. ‘Convenience’ is significant with the moderating effect of age, such that the effect is stronger for young people and ‘social influence’ is significant with the moderating effect of gender with a negative effect on males and a positive effect on females. Customer value co-creation intention shows a strong significant positive effect on co-creation practices and weak significant negative effect on value co-destruction. ‘Past experience’ displays a significant positive effect on co-creation practices and significant negative effect on co-destruction. Customer value co-creation practices show a significant positive effect on customers’ functional and emotional experiences, while co-destruction reveals a negative effect on emotional experiences, and surprisingly a positive effect on functional experiences. Finally, a significant positive effect of functional experiences is found on emotional experiences.This study adds new knowledge to marketing theory by revealing customer value co- creation practices in SSTs for the first time. It also makes some incremental contributions enriching the literature in the well-established fields of value co-creation, self-service technology and customer experience. Finally, the study develops a comprehensive conceptual model expounding co-creation intention, practices and experiences in self- service technologies, which can be extended to any technologically supported services, providing an element of scientific utility in the study. This understanding will benefit service providers in devising value enhancing self-service technological interfaces from both strategic and operational perspectives by ensuring superior customer experiences and ultimately accomplishing competitive advantages