On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Building a Roadmap for a Market Intelligence function in a Global B2B company

Tämän diplomityötutkimuksen tarkoituksena on luoda markkinaälyyn (MI) erikoistunut funktio suurelle, globaalisti toimivalle B2B-yritykselle. Tämän päivän muut-tuvilla markkinoilla, teollisuusyrityksen on oltava markkinalähtöinen selviytyäkseen. Markkinatiedon tehokas hyödyntäminen ei pelkästään luo tietoa markkinoista, vaan tuottaa kilpailukykyistä tietoa ja toimii strategisen päätöksenteon tukena pitkällä aikavälillä. Tämä tutkimus on kvalitatiivinen toimintatutkimus, joka sisältää kirjallisuuskat-sauksen, yritystapaustutkimuksen sekä syväanalyysin yrityksen MI-ympäristöstä. Kirjallisuuskatsaus pitää sisällään teoriaa liittyen markkinaälyyn useassa eri kon-tekstissa, asiakassuhteeseen, sekä prosessinmallintamiseen. Empiiriseen osaa seuraa tutkimusmenetelmäkappale, joka sisältää kaksivaiheisen tutkimuksen mukaan lu-kien 20 päällikkötason haastattelua sekä yhden laaja-alaisen työryhmätapaamisen. Työn tuloksena syntyy kolmivaiheinen tiekartta, jonka tarkoitus on toimia pohjana uuden MI-funktion rakentamiselle Case-yrityksessä. Tuloksen mukaan MI-funktio tulisi sijoittaa yrityksen asiakasrajapintaan sekä tukea yksiköiden välistä integraa-tiota. Markkinaälyn jakaminen yrityksen sisällä vaatii käytäntöjen, tarpeiden ja ta-voitteiden systemaattista viestintää eri organisaatiotasoille, jotta yritys voi edelleen saada asiakkaalta tarpeeseen vastaavaa tietoa. Viestintä yrityksen ja asiakkaan välil-lä on oltava molemminpuolista, jotta tulokset voisivat parantaa asiakassuhdetta. Kun asiakassuhde paranee, yritys voi oppia asiakkaalta arvokasta tietoa, markkinaälyä.

Facilitatory effects of an auditory warning stimulus in a visual location identification task and a visual shape identification task

The occurrence of a weak auditory warning stimulus increases the speed of the response to a subsequent visual target stimulus that must be identified. This facilitatory effect has been attributed to the temporal expectancy automatically induced by the warning stimulus. It has not been determined whether this results from a modulation of the stimulus identification process, the response selection process or both. The present study examined these possibilities. A group of 12 young adults performed a reaction time location identification task and another group of 12 young adults performed a reaction time shape identification task. A visual target stimulus was presented 1850 to 2350 ms plus a fixed interval (50, 100, 200, 400, 800, or 1600 ms, depending on the block) after the appearance of a fixation point, on its left or right side, above or below a virtual horizontal line passing through it. In half of the trials, a weak auditory warning stimulus (S1) appeared 50, 100, 200, 400, 800, or 1600 ms (according to the block) before the target stimulus (S2). Twelve trials were run for each condition. The S1 produced a facilitatory effect for the 200, 400, 800, and 1600 ms stimulus onset asynchronies (SOA) in the case of the side stimulus-response (S-R) corresponding condition, and for the 100 and 400 ms SOA in the case of the side S-R non-corresponding condition. Since these two conditions differ mainly by their response selection requirements, it is reasonable to conclude that automatic temporal expectancy influences the response selection process.