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Periodic-Frequent pattern mining is an empirical data mining technique that is used to investigate the customer purchase behavior pattern in the retail market. It provides the most extreme advantages to a retailer for product placements, product segmentation, store layout, selling strategies and different merchandising decisions to improve customer satisfaction as well as increase the sales. Traditionally, the single minimum support based frequent pattern mining approaches missed many lower supported items for high support threshold value, and on the other sites, the number of frequent patterns explode for low support threshold value. The retail market is highly seasonal, a number of items those are not periodic-frequent at all but those are periodic and frequent at a specific season, as results a huge number of seasonal periodic-frequent itemsets are remains out of reach. To resolve this problem, we propose an approach for extracting seasonally periodic-frequent patterns with user specified minimum support and maximum periodicity thresholds on multilevel retail supermarket dataset in this paper. The dataset has been created by collecting transaction slips in a Supermarket of Bangladesh. The results of our proposed approach extract many hidden seasonal patterns in transactional database for easy merchandising decisions and it shows the superiority over the traditional systems.

The Hodrick-Prescott filter is a convenient and therefore widely and routinely applied detrending method in macroeconomics working with empirical data. However, James Hamilton has recently gained attention with his vigorous advice against it and a proposal of a better alternative. Before abandoning Hodrick-Prescott and uncritically switching to the Hamilton regression filter, or before by force of habit ignoring Hamilton's contribution altogether, this paper, in a nontechnical and elementary manner, provides a little methodological reflection about the premisses behind the two approaches. In addition, it sets up a stylized oscillatory scenario in which the Hamilton filter dramatically misjudges the trend. On the other hand, it sketches a modification of the Hodrick-Prescott approach and also a search strategy that, at least under similar conditions, can help find a more appropriate degree of trend smoothing than the conventional choice of lambda = 1600 for quarterly data.

The purpose of this article is to identify, classify and contrast several types of online manufacturing platforms (OMPs), which are virtual platforms that connect and facilitate the interaction between two or more entities (e.g., firms and customers) in the manufacturing domain. We propose a taxonomy of OMPs emerging from the empirical data. To do so, we implement a multiple case study, triangulating data available on the web with interviews. We also use a novel type of experiential research: we perform some transactional activities (e.g., order the design and manufacture of a product) to better understand how the firms and their OMPs work. We select and assess the platforms of 71 firms in 21 different countries. The results suggest that there are closed online manufacturing platforms (COMPs), which optimize the industrial equipment and installations of major manufacturers and their clients, and multi-sided online manufacturing platforms (MOMPs), which connect customers with independent fabricators. This study provides insights that can help us to better understand the diversity and potential of OMP and the synergies that are created between them and manufacturing firms.

This paper proposes a macroscopic fluid modeling framework to assist with strategic decision making of a platform for operating a large-scale on-demand app-based ride-hailing system. The framework captures the spatiotemporal characteristics of a ride-hailing system, and is flexible in representing control policies that a platform is implementing. It thus enables the analysis of a large-scale ride-hailing system with observable market responses and facilitates the optimization of the control polices. As a demonstration of the proposed framework, we customize it for a ride-hailing system operated by Didi Chuxing in a large city of China, and conduct an empirical study of the system. In doing so, we calibrate the model with a high degree of granularity using empirical data, and then investigate optimal pricing strategies to achieve various managerial objectives of the platform. To our best knowledge, the proposed model is the first of its kind that offers a tractable way to support the analysis and optimization of large-scale ride-hailing systems. The empirical study also provides one of the first testbeds for examining various operations strategies for ride-hailing services.

We analyse the relative advocacy of competing approaches for the combination of investment signals in long/short portfolios. Specifically we study if it is preferable to (1) calculate weights for individual signals and then combine those weights (Mixed); or (2) combine signals and then calculate weights (Integrated). In our analysis we contrast insights obtained through a conceptual theoretical angle in simulations with a concrete application of Mixed and Integrated using empirical data to gain a broader perspective on the results. In both frameworks we find no meaningful performance differences between the methodologies. Transaction costs for the portfolio containing the combined signal are not significantly different between the two methodologies as long as trades are netted.

This article introduces new empirical data on the syntax of the biabsolutive construction in Lak that sheds new light on the analysis of this construction presented in Gagliardi et al. (2014). Some case-agreeing elements, such as compound anaphors, are shown to be able to bear ergative case despite the fact that no ergative DP is overtly present in the biabsolutive construction; this evidence necessitates a refinement of the structural analysis presented by Gagliardi et al., which precludes the possibility of ergative marking within the biabsolutive construction. I propose to capture the difference between ergative and biabsolutive constructions by exploiting a potential ambiguity in the content of the functional head Aux above AspP. On my account, the biabsolutive construction is understood as an instance of subject-to-subject raising with a reduced non-restructuring complement: the raising predicate ‘be involved in’ sits in Aux, assigning absolutive case to the closest DP in its c-command domain. All functional heads above AuxP thus bear gender agreement with the absolutive subject.

Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality suggests that some basic mechanisms may be responsible for the unfolding of human interactions in the physical space. Here we discuss a simple model that reproduces the empirical distributions for the individual, group and collective dynamics of face-to-face contact networks. The model describes agents that move randomly in a two-dimensional space and tend to stop when meeting ‘attractive’ peers, and reproduces accurately the empirical distributions.

Classical deterministic simulations of epidemiological processes, such as those based on System Dynamics, produce a single result based on a fixed set of input parameters with no variance between simulations. Input parameters are subsequently modified on these simulations using Monte-Carlo methods, to understand how changes in the input parameters affect the spread of results for the simulation. Agent Based simulations are able to produce different output results on each run based on knowledge of the local interactions of the underlying agents and without making any changes to the input parameters. In this paper we compare the influence and effect of variation within these two distinct simulation paradigms and show that the Agent Based simulation of the epidemiological SIR (Susceptible, Infectious, and Recovered) model is more effective at capturing the natural variation within SIR compared to an equivalent model using System Dynamics with Monte-Carlo simulation. To demonstrate this effect, the SIR model is implemented using both System Dynamics (with Monte-Carlo simulation) and Agent Based Modelling based on previously published empirical data., Proceedings of the 26th European Conference on Modelling and Simulation (ECMS), Koblenz, Germany, May 2012, pp 9-15, 2012

The success of an organization is measured by the term organization effectiveness. In the literature, the concept of union effectiveness attempts to indicate how well unions perform in achieving their goals and there is emphasis on the importance of using multiple criteria to assess organization effectiveness. However, only a few studies have utilized multidimensional measures of union effectiveness. This article explores the application of a comprehensive measure of union effectiveness at workplace. The authors use the Spatial Model (Quinn and Rohrbaugh, 1983) that employs complete and balanced indicators of effectiveness. Empirical data are provided from a research at postal companies in Indonesia and Malaysia.

The objective of this study is to demonstrate the degree to which debate about translation in the EU, and translation specifically of IFRS in the EU, generates both:  Deeply held convictions about language; and  Diversity of views on key issues even within translators into one language group. This study describes the empirics and method of data collection, and then offers detailed analysis of five issues faced by translators, drawing examples from each of the major language family groups in the EU. The data used in this study are derived from 109 responses to a survey of IFRS translators, members of IFRS translation committees or review panels, and textbook writers in the EU; undertaken in 2009. Each ‗Language Family Example‘ illustrates deeply-held convictions about language; and diversity of views even among highly experienced translators. These empirical data also illustrate translators‘ awareness that the ‗English‘ in which IFRS are written may impact on the ease or difficulties in translation. In nation-states where there is a relatively low level of foreign language study, there may be a greater number of accounting teachers, standard-setters, textbook writers and regulators who are unaware of such diversity and emotion. This study contributes towards understanding some key language issues during the IFRS convergence programme.

Ambidextrous organizations are supposed to innovate successfully both in case of evolutionary and revolutionary change through managing multiple and contradicting organizational architectures. This paper extends the theory on ambidextrous organizations through an explorative double case study of the structural and cultural aspects of successful incremental and radical innovations in one organization. Empirical data and theory are compared iteratively to define and elaborate the key concepts and patterns. We discuss four main findings on the management of the 'hardware', the structure, and 'software', the culture, of the ambidextrous organization.