Business Intelligence and Multi-market Competition

We consider a multi-market framework where a set of firms compete on two oligopolistic markets. The cost of production of each firm allows for spillovers across markets, ensuring that output decisions for both markets have to be made jointly. Prior to competing in these markets, firms can establish links gathering business intelligence about other firms. A link formed by a firm generates two types of externalities for competitors and consumers. We characterize the business intelligence equilibrium networks and networks that maximize social welfare. By contrast with single market competition, we show that in multi-market competition there exist situations where intelligence gathering activities are underdeveloped with regard to social welfare and should be tolerated, if not encouraged, by public authorities.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Il performance measurement negli enti locali. Strumenti innovativi nella prospettiva economico-aziendale

In un'epoca di risorse scarse e di crescente disaffezione verso la politica, l'azione degli enti locali ha un impatto sempre più rilevante sulla qualità della vita del cittadino. A tal fine, l'adozione di sistemi di programmazione e controllo, supportati da idonei strumenti, diviene essenziale per il perseguimento dell'efficienza e dell'efficacia e dunque per riconquistare la fiducia del cittadino stesso. Il volume, sulla base di un'analisi della normativa (dai primi anni Novanta fino al DL 174/2012 e s.m.i.) e della letteratura nazionale ed internazionale in tema di performance measurement, identifica un Modello ottimale (Modello PerformEL) per la redazione di due documenti che possono avere un ruolo centrale nel sistema di programmazione e controllo locale: il Piano e la Relazione sulla Performance. La capacità informativa di questi ultimi è testata tramite un'indagine empirica che ha coinvolto i comuni con almeno 50.000 abitanti, comparando struttura, forma e contenuti di tali documenti con quelli ritenuti ottimali e quindi inseriti nel Modello. Sulla base dei risultati dell'indagine, che mostrano una diffusa inadeguatezza informativa degli strumenti analizzati, viene proposto un percorso evolutivo per la graduale realizzazione di documenti di programmazione e controllo che, al di là della loro 'etichetta formale' (Piano della Performance piuttosto che Piano Esecutivo di Gestione, Relazione sulla Performance o Report dei Controlli interni) permetta di semplificare l'architettura informativa dell'ente locale (nel rispetto del DL 174/2012) e parimenti di trasformare i molteplici inutili adempimenti in utili documenti di performance measurement.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

What Happened to the ‘Development’ in Sustainable Development? Business Guidelines Two Decades After Brundtland

Over twenty years ago ‘Our Common Future’ presented a conceptualization and explanation of the concept of sustainable development. Since then numerous alternative definitions of the concept have been offered, of which at least some are exclusive to each other. At the same time, the role of business in the transition to sustainable development has increasingly received attention. Bringing these two trends in sustainable development together, this paper returns to the Brundtland version of the concept to examine to what extent the original principles of sustainable development are still embedded within key business guidelines, namely the UN Global Compact, the OECD Guidelines for Multinational Enterprises, the ICC Business Charter for Sustainable Development, the CAUX Principles, the Global Sullivan Principles and the CERES Principles. The findings suggest that these business guidelines tend to emphasize environmental rather than social aspects of sustainable development, in particular to the detriment of the original Brundtland prioritization of the needs of the poorest. Furthermore, the attention to environmental aspects stresses win-win situations and has a clear managerialist focus; whereas more conceptual environmental issues concerning systems interdependencies, critical thresholds or systemic limits to growth find little attention. The normative codes and principles targeted at the private sector thus not only add another voice to the multiple discourses on sustainable development but also contribute to a reinterpretation of the original agenda set by Brundtland towards conceptualizations of sustainable development around the needs of industrialised rather than developing countries. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment

Gender Diversity in the FTSE 100: The Business Case Claim Explored

This article examines the debate within corporate governance about the
appointment of female non-executive directors (NEDs). The first part
tracks the diversity story that corporate governance tells about itself from
the Cadbury Report (1992) to the Davies Report (2011). The second sets
out the evidence used to support the argument that female appointments
enhance profits and corporate profile. The third part presents the
authors' empirical analysis of FTSE 100 companies and female non-
executive board membership, and concludes that there is little evidence
that companies with female board membership display different charac-
teristics from those without. Industry sector emerges as a significant
factor in female appointments. The idea that women should be appointed
to boards to increase corporate profitability and profile is not strongly
supported by this analysis.A social justice argument based upon the right
of woman to equal economic participation opportunities provides a much
superior articulation of the need for boardroom diversity.

Emotional intelligence, personality and decoding non-verbal expressions of emotion

Previous research has highlighted theoretical and empirical links between measures of both personality and trait emotional intelligence (EI), and the ability to decode facial expressions of emotion. Research has also found that the posed, static characteristics of the photographic stimuli used to explore these links affects the decoding process and differentiates them from the natural expressions they represent. This undermines the ecological validity of established trait-emotion decoding relationships. This study addresses these methodological shortcomings by testing relationships between the reliability of participant ratings of dynamic, spontaneously elicited expressions of emotion with personality and trait EI. Fifty participants completed personality and self-report EI questionnaires, and used a computer-logging program to continuously rate change in emotional intensity expressed in video clips. Each clip was rated twice to obtain an intra-rater reliability score. The results provide limited support for links between both trait EI and personality variables and how reliably we decode natural expressions of emotion. Limitations and future directions are discussed.