A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

Gender and the business cycle: an analysis of labour markets in the US and UK

Starting from an improved understanding of the relationship between gender labour market stocks and the business cycle, we analyse the contributing role of flows in the US and UK. Focusing on the post 2008 recession period, the subsequent greater rise in male unemployment can mostly be explained by a less cyclical response of flows between employment and unemployment for women, especially the entry into unemployment. Across gender and country, the inactivity rate is generally not sensitive to the state of the economy. However, a flows based analysis reveals a greater importance of the participation margin over the cycle. Changes in the rates of flow between unemployment and inactivity can each account for around 0.8-1.1 percentage points of the rise in US male and female unemployment rates during the latest downturn. For the UK, although the participation flow to unemployment similarly contributed to the increase of the female unemployment rate, this was not the case for men. The countercyclical flow rate from inactivity to employment was also more significant for women, especially in the US, where it accounted for approximately all of the fall in employment, compared with only 40% for men.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Site-specific and geographical segmental social, environmental and ethical disclosures by the Ghanaian mining sector

Purpose: This paper explores the extent of site-specific and geographic segmental social, environmental and ethical reporting by mining companies operating in Ghana. We aim to: (i) establish a picture of corporate transparency relating to geographic segmentation of social, environmental and ethical reporting which is specific to operating sites and country of operation, and; (ii) gauge the impact of the introduction of integrated reporting on site-specific social, environmental and ethical reporting. Methodology/Approach: We conducted an interpretive content analysis of the annual/integrated reports of mining companies for the years 2009, 2010 and 2011 in order to extract site-specific social, environmental and ethical information relating to the companies’ mining operations in Ghana. Findings and Implications: We found that site-specific social, environmental and ethical reporting is extremely patchy and inconsistent between the companies’ reports studied. We also found that there was no information relating to certain sites, which were in operation, according to the Ghana Minerals Commission. This could simply be because operations were not in progress. Alternatively it could be that decisions are made concerning which site-specific information is reported according to a certain benchmark. One policy implication arising from this research is that IFRS should require geographic segmental reporting of material social, environmental and ethical information in order to bring IFRS into line with global developments in integrated reporting. Originality: Although there is a wealth of sustainability reporting research and an emergent literature on integrated reporting, there is currently no academic research exploring site-specific social, environmental and ethical reporting

Enterprise intelligence: searching for a single version of the truth

Multiple versions of information and associated problems are well documented in both academic research and industry best practices. Many solutions have proposed a single version of the truth, with Business intelligence being adopted by many organizations. Business Intelligence (BI), however, is largely based on the collection of data, processing and presentation of information to meet different stakeholders’ requirement. This paper reviews the promise of Enterprise Intelligence, which promises to support decision-making based on a defined strategic understanding of the organizations goals and a unified version of the truth.

Causal relationship between obesity and vitamin D status: bi-directional mendelian randomization analysis of multiple cohorts

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Numbers in motion

We explore the debates surrounding the constructive and discursive capabilities of accounting information focusing in particular on the reception volatility of numbers once they are produced and ‘exposed’ to various communities of minds. Drawing on Goffman’s (1974) frame analysis and Vollmer’s (2007) work on the three-dimensional character of numerical signs, we explore how numbers can go through gradual or instantaneous transformations, get caught up in public debates and become ‘agents’ or ‘captives’ in creating social order and in some cases social drama. In our analysis we also relate to the work of Durkheim (1993, 2002) on the sociology of morality to illustrate how numbers can become indicators of moral transgression. The study explores both historical and contemporary examples of controversies and recent accounting scandals to demonstrate how preparers (of financial information) can lose control over numbers which then acquire new meanings through social context and collective (re)framing. The main contribution of the study is to illustrate how the narratives attached to numbers are malleable and fluid across both time and space.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Towards the design of a unified semantics model for OLTP and OLAP systems

The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.

Shifting sand, shifting livelihoods? Reflections on a coastal gold rush in Ghana

Artisanal and small-scale mining (ASM) is often characterised as rush-type activity undertaken by people looking to ‘get-rich quick’. An alternative view posits ASM as poverty-driven activity which provides a valuable source of employment to a rural population where agriculture has failed to provide an adequate income. Against this dichotomy, this article critically reviews the short-lived, but high profile, gold rush which occurred on the beaches of Elmina, a fishing town in Ghana’s Central Region. At its peak, more than 1000 people, including local fishermen and career miners from the Western Region and Eastern Region of the country, were mining on the beaches. Drawing on interviews with miners and local business owners, the analysis explores the dynamics of the rush and its implications for understanding the ASM sector in Ghana. The discussion highlights the challenges associated with managing resources in dynamic and heterogeneous contexts, reconciling separate and conflicting sectoral priorities and the need to go beyond simplified and dualistic representations of the sector.

Improving aircraft maintenance, repair, and overhaul: A novel text mining approach

Aircraft Maintenance, Repair and Overhaul (MRO) feedback commonly includes an engineer’s complex text-based inspection report. Capturing and normalizing the content of these textual descriptions is vital to cost and quality benchmarking, and provides information to facilitate continuous improvement of MRO process and analytics. As data analysis and mining tools requires highly normalized data, raw textual data is inadequate. This paper offers a textual-mining solution to efficiently analyse bulk textual feedback data. Despite replacement of the same parts and/or sub-parts, the actual service cost for the same repair is often distinctly different from similar previously jobs. Regular expression algorithms were incorporated with an aircraft MRO glossary dictionary in order to help provide additional information concerning the reason for cost variation. Professional terms and conventions were included within the dictionary to avoid ambiguity and improve the outcome of the result. Testing results show that most descriptive inspection reports can be appropriately interpreted, allowing extraction of highly normalized data. This additional normalized data strongly supports data analysis and data mining, whilst also increasing the accuracy of future quotation costing. This solution has been effectively used by a large aircraft MRO agency with positive results.

Untangling rhetoric and reality in the CSR debate – the role of corporate social responsibility in effective business strategy

While there is a strong moral case for corporate social responsibility (CSR), the business case for CSR is certainly not irrefutable. A better understanding of how to integrate CSR into business strategy is needed but with ever increasing momentum towards sustainability as a business driver, it is often difficult to untangle the rhetoric from reality in the CSR debate. Through an analysis of eight case studies of leading firms from throughout the construction supply chain who claim to engage in CSR, we explore how consulting and contracting firms in the construction and engineering industries integrate CSR into their business strategy. Findings point to an inherent caution of moving beyond compliance and to a risk-averse culture which adopts very narrow definitions of success. We conclude that until this culture changes or the industry is forced by clients or regulation to change, the idea of CSR will continue to mean achieving economic measures of success, with ecological goals a second regulated priority and social goals a distant third.