Pekka Malo

Pekka Malo
Aalto University · Department of Information and Service Economy

Associate Professor

About

68
Publications
49,959
Reads
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1,820
Citations
Citations since 2017
27 Research Items
1527 Citations
20172018201920202021202220230100200300
20172018201920202021202220230100200300
20172018201920202021202220230100200300
20172018201920202021202220230100200300
Additional affiliations
May 2012 - present
Aalto University
Position
  • Professor (Assistant)

Publications

Publications (68)
Article
In proceeding beyond the generic optimal rotation model, forest economic research has applied various specifications that aim to circumvent the problems of high dimensionality. We specify an age- and size-structured mixed-species optimal harvesting model with binary variables for harvest timing, stochastic stand growth, and stochastic prices. Reinf...
Article
Digital trace data derived from organizations’ information systems represent a wealth of possibilities in analyzing decision-making processes and organizational performance. While data-mining methods have advanced considerably over recent years, organizational process research has rarely analyzed this type of trace data with the objective of better...
Article
Fine‐grained financial sentiment analysis on news headlines is a challenging task requiring human‐annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple entities are present in a news headline. In an effort to further research in this area, we make publicly ava...
Article
Full-text available
By advancement in digital marketing, business-to-business (B2B) buyers carry out over half of the buying process through digital touchpoints before they establish any significant contact with the B2B seller. Knowing the buying stage of a potential buyer can bring a substantial advantage to the B2B seller given the complexity of the transaction and...
Article
Full-text available
We solve a stochastic high-dimensional optimal harvesting problem by reinforcement learning algorithms developed for agents who learn an optimal policy in a sequential decision process through repeated experience. This approach produces optimal solutions without discretization of state and control variables. Our stand-level model includes mixed spe...
Article
Full-text available
The paper presents an approach for implementing inscrutable (i.e., nonexplainable) artificial intelligence (AI) such as neural networks in an accountable and safe manner in organizational settings. Drawing on an exploratory case study and the recently proposed concept of envelopment, it describes a case of an organization successfully "enveloping"...
Preprint
Full-text available
Synthetic control method (SCM) identifies causal treatment effects by constructing a counterfactual treatment unit as a convex combination of donors in the control group, such that the weights of donors and predictors are jointly optimized during the pre-treatment period. This paper demonstrates that the true optimal solution to the SCM problem is...
Article
Business-to-business (B2B) sellers need to enhance content marketing and analytics in an online environment. The challenge is that sellers have data but do not know how to utilize it. In this study, we develop a neural content model to match the content that B2B sellers are providing with the type of content that buyers are seeking. The model was t...
Article
Huge increases in computing capacity and data volumes have spurred the development of applications that use artificial intelligence (AI), a technology that is being implemented for increasingly complex tasks, from playing Go to screening for cancer. Private and public businesses and organizations are deploying AI applications to process vast quanti...
Chapter
Population-based optimization algorithms, such as evolutionary algorithms, have enjoyed a lot of attention in the past three decades in solving challenging search and optimization problems. In this chapter, we discuss recent population-based evolutionary algorithms for solving different types of bilevel optimization problems, as they pose numerous...
Preprint
Full-text available
The synthetic control method (SCM) is a major innovation in the estimation of causal effects of policy interventions and programs in a comparative case study setting. In this paper, we demonstrate that the data-driven approach to SCM requires solving a bilevel optimization problem. We show how the SCM problem can be solved using iterative algorithm...
Conference Paper
Sustainable forest management is a crucial element in combating climate change, plastic pollution, and other unsolved challenges of the 21st century. Forests not only produce wood - a renewable resource that is increasingly replacing fossil-based materials - but also preserve biodiversity and store massive amounts of carbon. Thus, a truly optimal f...
Article
Full-text available
A large number of application problems involve two levels of optimization, where one optimization task is nested inside the other. These problems are known as bilevel optimization problems and have been studied by both classical optimization community and evolutionary optimization community. Most of the solution procedures proposed until now are ei...
Chapter
Full-text available
Computational finance is one of the fastest-growing application areas for natural language processing technologies. Already today, algorithmic trading funds are successfully using robo readers and sentiment analysis techniques to support adaptive algorithms that are capable of making automated decisions with little or no human intervention. However...
Preprint
This paper focuses on the simulation of a buying process and further estimation of its hidden stages in online B2B markets via a proposed statistical modeling technique. In recent decades, business to business (B2B) buying has become more digital-centric and buyer-driven than before. More than half of the B2B buying process is carried out through...
Preprint
Structural change detection problems are often encountered in analytics and econometrics, where the performance of a model can be significantly affected by unforeseen changes in the underlying relationships. Although these problems have a comparatively long history in statistics, the number of studies done in the context of multivariate data under...
Article
Full-text available
An online poker site is a good example of a dual-purposed information system that is used for both fun and making money. In this study, we address the platform selection problem associated with online poker sites by investigating the features online gamers value when selecting a platform. We test the differences in preferences for online gaming pla...
Article
Many objective optimization problems have turned out to be a considerable challenge for evolutionary algorithms due to the difficulty of finding and visualizing high-dimensional Pareto frontiers. Fortunately, however, the task can be simplified whenever an interaction with a human decision maker is possible. Instead of finding the entire Pareto fro...
Conference Paper
Full-text available
Rather than viewing television shows one episode at a time, many people now consume them back-to-back. While this is in itself a unique practice, it manifests in various forms, two of which seem to enjoy great popularity: ‘bingeing’ and ‘marathoning’. In this study, we explore their association with online television streaming services and schedule...
Article
Voting Advice Applications (VAAs) are online decision support systems that try to match voters with political parties or candidates in elections, typically based on how each responds to a number of policy issue statements. Such VAAs play a major role in many countries. In this paper, we describe the development and large-scale application of a new...
Article
We show that contextual variables in a Multiple Criteria Decision Making task influence choice quality. Based on an experiment we investigate the effects of product type, emotional attachment, and the amount and structure of information provided. We measured choice quality with nondominance, which is a desirable property of good choices. Regarding...
Conference Paper
The problem of detecting structural changes in a regression study has become crucially important in a wide variety of fields, since data generating processes in a real world are usually unstable. Taking into account the fact that relationships within observed data are often in a continuous flux, it can be challenging to make any distributional assu...
Article
Full-text available
Bilevel optimization is defined as a mathematical program, where an optimization problem contains another optimization problem as a constraint. These problems have received significant attention from the mathematical programming community. Only limited work exists on bilevel problems using evolutionary computation techniques; however, recently ther...
Article
Simulated virtual realities offer a promising but currently underutilized source of data in studying cultural and demographic aspects of dynamic decision-making (DDM) in small groups. This study focuses on one simulated reality, a clock-driven business simulation game, which is used to teach operations management. The purpose of our study is to ana...
Chapter
Bilevel optimization involves two levels of optimization where one optimization level acts as a constraint to another optimization level. There are enormous applications that are bilevel in nature; however, given the difficulties associated with solving this difficult class of problem, the area still lacks efficient solution methods capable of hand...
Article
Bilevel optimization problems are a class of challenging optimization problems, which contain two levels of optimization tasks. In these problems, the optimal solutions to the lower level problem become possible feasible candidates to the upper level problem. Such a requirement makes the optimization problem difficult to solve, and has kept the res...
Article
A significant amount of research has been done on bilevel optimization problems both in the realm of classical as well as evolutionary optimization. However, the multiobjective extensions of bilevel programming has received relatively little attention from researchers in both the domains. The existing algorithms are mostly brute-force nested strate...
Article
A shift from even-aged forest management to uneven-aged management practices leads to a problem rather different from the existing straightforward practice that follows a rotation cycle of artificial regeneration, thinning of inferior trees and a clearcut. A lack of realistic models and methods suggesting how to manage uneven-aged stands in a way t...
Conference Paper
Cloud computing remains an increasingly popular topic among practitioners as well as researchers. The literature spans across multiple disciplines, and the knowledge is fragmented and not systematized. To address this issue we apply topic models to conduct a meta-review on cloud computing. We identify twenty research topics across multiple discipli...
Conference Paper
Bilevel decision making and optimization problems are commonly framed as leader-follower problems, where the leader desires to optimize her own decision taking the decisions of the follower into account. These problems are known as Stackelberg problems in the domain of game theory, and as bilevel problems in the domain of mathematical programming....
Article
Full-text available
Variable selection is recognized as one of the most critical steps in statistical modeling. The problems encountered in engineering and social sciences are commonly characterized by over-abundance of explanatory variables, non-linearities and unknown interdependencies between the regressors. An added difficulty is that the analysts may have little...
Article
Bilevel optimization problems are characterized by a hierarchical leader-follower structure, where the leader desires to optimize her own strategy taking the response of the follower into account. These problems are referred to as Stackelberg problems in the domain of game theory, and as bilevel problems in the domain of mathematical programming. I...
Article
In this paper, we provide an improved evolutionary algorithm for bilevel optimization. It is an extension of a recently proposed Bilevel Evolutionary Algorithm based on Quadratic Approximations (BLEAQ). Bilevel optimization problems are known to be difficult and computationally demanding. The recently proposed BLEAQ approach has been able to bring...
Article
Full-text available
Many of the modern optimization algorithms contain a number of parameters that require tuning before the algorithm can be applied to a particular class of optimization problems. A proper choice of parameters may have a substantial effect on the accuracy and efficiency of the algorithm. Until recently, parameter tuning has mostly been performed usin...
Article
The use of robo-readers to analyze news texts is an emerging technology trend in computational finance. In recent research, a substantial effort has been invested to develop sophisticated financial polarity-lexicons that can be used to investigate how financial sentiments relate to future company performance. However, based on experience from other...
Article
Full-text available
Abstract In this paper, we propose a procedure for designing controlled test problems for single-objective bilevel optimization. The construction procedure is flexible and allows its user to control the different complexities that are to be included in the test problems independently of each other. In addition to properties that control the difficu...
Conference Paper
Full-text available
Rapid development of natural language processing technologies has paved way for automatic sentiment analysis and emergence of robo-readers in computational finance. However, the technology is still in its nascent state. Distilling sentiment information from unstructured sources has turned out to be a complicated and strongly domain-dependent proble...
Article
Stackelberg games are a classic example of bilevel optimization problems, which are often encountered in game theory and economics. These are complex problems with a hierarchical structure, where one optimization task is nested within the other. Despite a number of studies on handling bilevel optimization problems, these problems still remain a cha...
Conference Paper
Full-text available
Bilevel programming problems are often found in practice. In this paper, we handle one such bilevel application problem from the domain of environmental economics. The problem is a Stakelberg game with multiple objectives at the upper level, and a single objective at the lower level. The leader in this case is the regulating authority, and it tries...
Article
Full-text available
Bilevel optimization problems are a class of challenging optimization problems, which contain two levels of optimization tasks. In these problems, the optimal solutions to the lower level problem become possible feasible candidates to the upper level problem. Such a requirement makes the optimization problem difficult to solve, and has kept the res...
Article
Most of the existing information retrieval systems are based on bag-of-words model and are not equipped with common world knowledge. Work has been done towards improving the efficiency of such systems by using intelligent algorithms to generate search queries, however, not much research has been done in the direction of incorporating human-and-soci...
Conference Paper
Stackelberg games have been widely studied in the literature and are a perfect real- world example of a bilevel optimization problem. The hierarchical nature of the problem makes it difficult to arrive at the optimal solution using the existing methodologies. Approximate solution techniques are commonly employed to handle such models with simplifyi...
Conference Paper
Full-text available
In this paper, we propose a set of six test problems for single-objective bilevel optimization. The test-collection represents various difficulties which are commonly encountered in practical bilevel optimization problems. To support experiments with problems of different size, all of the test problems are scalable in terms of the number of variabl...
Article
In this article, we propose a new concept-based method for document classification. The conceptual knowledge associated with the words is drawn from Wikipedia. The purpose is to utilize the abundant semantic relatedness information available in Wikipedia in an efficient value function-based query learning algorithm. The procedure learns the value f...
Conference Paper
Full-text available
The curse of dimensionality is a well-recognized problem in the field of document filtering. In particular, this concerns methods where vector space models are utilized to describe the document-concept space. When performing content classification across a variety of topics, the number of different concepts (dimensions) rapidly explodes and as a re...
Article
Full-text available
The use of domain knowledge is generally found to improve query efficiency in content filtering applications. In particular, tangible benefits have been achieved when using knowledge-based approaches within more specialized fields, such as medical free texts or legal documents. However, the problem is that sources of domain knowledge are time consu...
Article
Full-text available
Most of the existing information retrieval systems are based on bag of words model and are not equipped with common world knowledge. Work has been done towards improving the efficiency of such systems by using intelligent algorithms to generate search queries, however, not much research has been done in the direction of incorporating human-and-soci...
Article
Full-text available
This paper proposes a parametric approach for stochastic modeling of limit order markets. The models are obtained by augmenting classical perfectly liquid market models by few additional risk factors that describe liquidity properties of the order book. The resulting models are easy to calibrate and to analyze using standard techniques for multivar...
Conference Paper
Full-text available
The use of domain knowledge is generally found to improve query efficiency in content filtering applications. In particular, tangible benefits have been achieved when using knowledge-based approaches within more specialized fields, such as medical free texts or legal documents. However, the problem is that sources of domain knowledge are time- cons...
Article
Electricity prices are known to exhibit multifractal properties. We accommodate this finding by investigating multifractal models for electricity prices. In this paper we propose a flexible Copula-MSM (Markov Switching Multifractal) approach for modeling spot and weekly futures price dynamics. By using a conditional copula function, the framework a...
Article
Full-text available
A considerable problem in statistics and risk management is finding distributions that capture the complex behaviour exhibited by financial data. The importance of higher order moments in decision making has been well recognized and there is increasing interest in modelling with distributions that are able to account for these effects. The Pearson...
Article
Full-text available
This article considers a variety of specification tests for multivariate GARCH models that are used for dynamic hedging in electricity markets. The test statistics include the robust conditional moments tests for sign-size bias along with the recently introduced copula tests for an appropriate dependence structure. We consider this effort worthwhil...
Article
The recent research of turbulent cascades in hydrodynamics has inspired the newly emerged field of econophysics to develop multifractal pro- cesses as a competitive alternative to the standard models of continuous time finance. The essential new features of these models are their scale invariance, multiscaling, and clustering in volatility. In this...
Article
Full-text available
Although Conditional Value-at-Risk has signiflcant advantages over traditional risk measures such as Value-at-Risk, it has not been adopted by practitioners as quickly as expected. One of the reasons slowing down its progress has been the lack of simple tools for its computation. In this paper we consider calculating CVaR when the underlying asset...

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Projects (2)
Project
In this project, we develop new techniques to address the different challenges in online business to business (B2B) marketing.