| 1. |
- Carling, Kenneth, 1967-
(author)
-
A comment on outlier detection and skewed distributions
- 2017
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Reports (other academic/artistic)abstract
- It seems that a paper of mine appearing in Computational Statistics & Data Analysis (Carling, 2000) has prompted the development of outlier detection methods for highly skewed data. However, I wrote the paper in the spirit of Exploratory Data Analysis (Tukey, 1977) and I shared Tukey’s opinion, and I still hold it, that skewed data are better to be transformed for approximate symmetry prior to detection of outliers (or other data analyses).
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| 2. |
- Carling, Kenneth, 1967-, et al.
(author)
-
A stopping rule while searching for optimal solution of facility-location
- 2013
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Reports (other academic/artistic)abstract
- Solutions to combinatorial optimization, such as p-median problems of locating facilities, frequently rely on heuristics to minimize the objective function. The minimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. However, pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small branch of the literature suggests using statistical principles to estimate the minimum and use the estimate for either stopping or evaluating the quality of the solution. In this paper we use test-problems taken from Baesley's OR-library and apply Simulated Annealing on these p-median problems. We do this for the purpose of comparing suggested methods of minimum estimation and, eventually, provide a recommendation for practioners. An illustration ends the paper being a problem of locating some 70 distribution centers of the Swedish Post in a region.
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| 3. |
- Carling, Kenneth, 1967-, et al.
(author)
-
Data-sharing SME, Last-Mile Delivery LivingLab : a FEDeRATED LivingLab
- 2024
-
In: FoI - Digitaliserade sammodala hållbara transportkedjor, Living Labs i projekt FEDeRATED. - Borlänge : Trafikverket. - 9789180453226
-
Book chapter (other academic/artistic)abstract
- This Data-sharing SME, Last-Mile Delivery LivingLab focuses on the last-mile (LM) transport setting. The LivingLab involves actors such as last-mile couriers, traditional delivery companies, retailers, and terminal companies. The LivingLab is one of 23 under the EU project FEDeRATED (www.federatedplatforms.eu), which aims to foster and achieve digital co-operation in logistics. Stakeholder engagement is required to achieve open data sharing in the interests of improving the operational efficiency of delivery. This LivingLab identifies that the last-mile couriers dispute the benefits of data sharing, while being pushed towards data sharing by (environmental) regulations and other market forces. However, and somewhat in contradiction, a considerable number of the couriers voluntarily associate themselves with a semi-Federated system of open and neutral data sharinginfrastructure. The financial gains for these couriers have been substantial.
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| 4. |
- Carling, Kenneth, 1967-, et al.
(author)
-
Market integration in Nordic online retail markets : Do cross-border transaction costs still matter?
- 2023
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Reports (other academic/artistic)abstract
- If online retail markets are integrated, in that cost shocks in one country also affect pricing in other countries, asymmetric shocks to any one country in the region will spill over to neighboring countries as well. Using web-scraped productlevel prices from a group of retail firms selling identical products in at least two of the four Nordic markets under study, we investigate if national markets are segmented at the borders. Contrary to previous studies, we use differences in product characteristics to divide the data into products that are easily transported across borders and those that are not. At the extreme end of the transportability spectrum, we investigate market integration for four types of games for computers or game consoles that are delivered via downloads, where the cross-border transaction costs should be close to zero. Our results show that markets for product categories where cross-border transaction costs are high are also segmented at the border, while markets for product categories that can easily be traded andtransported between countries are not. We find an even higher level of market integration for games delivered via downloads than for the same games sold through traditional channels. As such, cross-border transaction costs still matter for market segmentation, but only for the sub-set of products where such costs are high.
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| 5. |
- Carling, Kenneth, 1967-, et al.
(author)
-
Minimizing travel distance and CO2 emissions when reconfiguring retail store networks
- 2024
-
Reports (other academic/artistic)abstract
- Retail chains continually expand, reconfigure, and contract their store networks to serve their customers and maximize profits. One notable consequence of these actions is changes in the distances between consumers’ residences andnearest stores, altering their transportation-related CO2 emissions. Therefore, this study aims to examine the environmental impact of the reconfiguration of the IKEA store network in Sweden during the twenty-first century and compare the actual reconfiguration to one that minimizes consumers’ travel distances and, thus, CO2emissions. The expansion of the IKEA network in Sweden between 2004 and 2016, adding four (2004–2007) and then three (2013–2016) additional stores, reduced consumers’ average travel distance to their nearest store from 87 to 65.2 km. However, had IKEA managers used our web-available decision support tool,eCOmpass, this reduction could have been achieved after the first round of store additions since the distance-minimizing locations for the four new stores established in 2004–2007 would have reduced average travel distance to 64.9 km.
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| 6. |
- Carling, Kenneth, 1967-, et al.
(author)
-
On deploying eCOmpass : a decision support tool for environmentally friendly retail locations
- 2024
-
Reports (other academic/artistic)abstract
- Much focus in the joint retailing and transportation domain has been on the transition to e-tailing and the reformation of supply-chain logistics. However, traditional retailing, where consumers visit stores for shopping, dominates and will continue to do so for the foreseeable future. Retailers continuously expand, contract, and reconfigure their store network for strategic reasons. This paper reports on a project aiming to facilitate the incorporation of environmental consequences into the retailer’s reconfiguration decision process. It describes the design and deployment process of eCOmpass, an online decision support tool that enables retailers to estimate the change in transportation-related CO2 emissions caused by a reconfiguration of their store network. This description encompasses the judgmental choices of data acquisition, optimization technology, and user interface.
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| 7. |
- Carling, Kenneth, 1967-
(author)
-
On leading and making data-driven decisions, or not
- 2019
-
In: Developing Informed Intuition for Decision Making. - : Taylor & Francis Group. - 9780367258573 - 9780429298097 ; , s. 161-173
-
Book chapter (peer-reviewed)abstract
- In this chapter, I consider the cognitive biases arising in judgment under uncertainty that jeopardize good decision-making aligned with normative decision theories. This problem raises objections towards intuitive and fast decision-making. It would be appealing if training could be devised for reducing the biases, and I argue that such training is feasible. I relate best-practice in such training and advocate a number of topics to be included in such training for good, intuitive decision-making skills.
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| 8. |
- Carling, Kenneth, 1967-, et al.
(author)
-
Privacy and data : Some research venues
- 2021
-
In: A Research Agenda for Knowledge Management and Analytics. - : Edward Elgar Publishing. - 9781800370623 - 9781800370616 ; , s. 191-203
-
Book chapter (peer-reviewed)abstract
- The issue of data privacy is often reduced to secure data transactions by cryptographic techniques. However, in a liberal democracy the issue of privacy connects to fundamental questions about the co-existence and collaboration between its citizens. One is the conflict between self-interest and the interest of the commons, whereby research on privacy topics is found in distant and disparate research streams. Sharing of data perceived as private may drastically increase collective welfare, while reducing it for single citizens. In this chapter, we present a metaphor to highlight the fundamentals of privacy and explain how the access to new data-processing technologies provokes new questions to be addressed. Furthermore, we illustrate how various research streams differ in presumptions and privacy topics of interest, and we stress the potential knowledge-producing value of bridging these streams. We end by pointing out some particularly interesting research venues for privacy and data. © Jay Liebowitz 2021.
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| 9. |
- Carling, Kenneth, 1967-, et al.
(author)
-
The effect on CO2 emissions of taxing truck distance in retail transports
- 2017
-
In: Transportation Research Part A. - : Elsevier. - 0965-8564 .- 1879-2375. ; 97, s. 47-54
-
Journal article (peer-reviewed)abstract
- To finance transportation infrastructure and to address social and environmental negative externalities of road transports, several countries have recently introduced or consider a distance based tax on trucks. In competitive retail and transportation markets, such tax can be expected to lower the demand and thereby reduce CO2 emissions of road transports. However, as we show in this paper, such tax might also slow down the transition towards e-tailing. Considering that previous research indicates that a consumer switching from brick-and-mortar shopping to e-tailing reduces her CO2 emissions substantially, the direction and magnitude of the environmental net effect of the tax is unclear. In this paper, we assess the net effect in a Swedish regional retail market where the tax not yet is in place. We predict the net effect on CO2 emissions to be positive, but off-set by about 50% because of a slower transition to e-tailing.
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| 10. |
- Carling, Kenneth, 1967-
(author)
-
The emergence of Microdata Analysis and its intellectual history over the past two decades
- 2021
-
Reports (other academic/artistic)abstract
- By 2020, students of Dalarna University had produced some 100 Bachelor and Master’s theses and 25 Licentiate or Doctoral theses in the academic discipline of Microdata Analysis guided by the university’s faculty. While firmly rooted in the tradition and the format of the formal sciences Computer Science and Mathematics, the theses are disparate with regard to area of investigation, research method, and epistemology. The research carried out in these theses is recognized internationally by learned societies and their journals and conferences, yet Dalarna University remains globally unique in labelling an academic discipline Microdata Analysis. This paper attempts to narrate the history of the forming process of Microdata Analysis at the university and grasp its nature.
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| 11. |
- Carling, Kenneth, 1967-, et al.
(author)
-
The Power of the Synthetic Control Method
- 2016
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Reports (other academic/artistic)abstract
- The synthetic control method (SCM) is a new, popular method developed for the purpose of estimating the effect of an intervention when only one single unit has been exposed. Other similar, unexposed units are combined into a synthetic control unit intended to mimic the evolution in the exposed unit, had it not been subject to exposure. As the inference relies on only a single observational unit, the statistical inferential issue is a challenge. In this paper, we examine the statistical properties of the estimator, study a number of features potentially yielding uncertainty in the estimator, discuss the rationale for statistical inference in relation to SCM, and provide a Web-app for researchers to aid in their decision of whether SCM is powerful for a specific case study. We conclude that SCM is powerful with a limited number of controls in the donor pool and a fairly short pre-intervention time period. This holds as long as the parameter of interest is a parametric specification of the intervention effect, and the duration of post-intervention period is reasonably long, and the fit of the synthetic control unit to the exposed unit in the pre-intervention period is good.
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| 12. |
- Espegren, Yanina, et al.
(author)
-
Smart online grocery delivery and peri-urbanconsumers’ attitudes
- 2018
-
Reports (other academic/artistic)abstract
- Purpose: To explore consumers’ attitudes towards e-commerce, in particular online grocery shopping, and its delivery in non-dense areas for the purpose of designing smart last-mile solutions.Approach: The state-of-the-art of smart e-commerce delivery in dense areas was identified by a review of the literature. It was expected that this knowledge could be transferred to non-dense areas. This prediction was examined and explored further by making use of four focus groups recruited in a Swedish mid-sized town.Findings: Respondents were generally positive towards e-commerce, although mixed attitudes were found with regard to online grocery shopping. Further, the willingness to pay for flexible, smart and sustainable delivery was low, with a notable exception for local produce.Originality: The knowledge acquired and solution developed in dense areas is not readily transferred to non-dense areas. There is scope for developing new Business Models for the supply chain of local produce. For the prototype testing and roll-out of smart e-commerce delivery platforms, the online local produce market is recommended.
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| 13. |
- Grek, Åsa, 1989-
(author)
-
Firm Policies and Critical Data Sources
- 2024
-
Doctoral thesis (other academic/artistic)abstract
- In the dynamic fluctuating economic landscape, firm policies are the guiding principles that steer market conditions and firms' behaviour. In the past, these policies were formulated based on limited data and a heavy reliance on expert opinions. However, a new era is dawning, characterised by vast amounts of data processing using advanced statistical and computer science methodologies. Data-driven decision-making uses these methodologies to consolidate and process data into actionable information, leading to firm policies. The critical data sources are the data sources on which the policies are based. The data-driven decision-making allows the data to speak for itself, relying less on expert opinions for policymaking. However, it also necessitates a higher requirement of validation. This thesis investigates five different cases of firm policy and critical data sources. Each one of them will present one aspect of this broad topic. The first paper investigates selecting auxiliary variables to estimate firm characteristics, aiming to reduce bias and improve accuracy. Simple variables outperform complex ones, and complete data enhances accuracy. The second paper introduces a methodology for quantitative inductive research on ordinal survey data by new- and traditional- penalising methods. The new methods outperformed the old and could find a significant variable, while the older models could not. The third paper examines how macro-factors impacted various Small and Medium Enterprises (SME) sectors in the European Union’s member states from 2005 to 2019. The research offers valuable insights for policymakers and business leaders, aiding in tailored policy interventions and support mechanisms to address regional disparities and economic conditions. The fourth and fifth papers investigated Short-Time Work (STW), a primary policy tool during the COVID-19 pandemic. These studies used Swedish firm-level data to assess the STW policy. In the fourth paper, STW was associated with a reduction in employee numbers and a slightly increased productivity level compared to non-STW firms. In the fifth paper, STW did not increase the survival of SMEs. In conclusion, the ever-evolving economic landscape necessitates data-driven decision-making for informed actions and policymaking. This thesis is by no means a complete investigation, and further research is needed on this topic.
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| 14. |
- Han, Mengjie, 1985-, et al.
(author)
-
GRASP and Statistical Bounds for Heuristic Solutions to Combinatorial Problems
- 2019
-
In: International Journal of Management and Applied Science. - : Institute of Research and Journals (IRAJ). - 2394-7926. ; 5:8, s. 113-119
-
Journal article (peer-reviewed)abstract
- The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few heuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds have previously been found reliable when obtained from the Genetic algorithm whereas in this work they have been found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.
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| 15. |
- Han, Mengjie, 1985-
(author)
-
Heuristic optimization of the p-median problem and population re-distribution
- 2013
-
Doctoral thesis (other academic/artistic)abstract
- This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution. The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis. Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling.
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| 16. |
- Huq, Asif M
(author)
-
Corporate Disclosures Regulations : Social Solution or a Problem?
- 2021
-
Doctoral thesis (other academic/artistic)abstract
- Regulations are argued to have the answer to solving various social and economic problems that society faces today (e.g., climate change, tax evasion, etc.). However, regulations may instead become the problem (e.g., overregulation). The central research question of this doctoral thesis is “are corporate disclosures regulations a social solution or a problem?” To answer the central research question, Papers I and II examine the economic effects of an EU-wide audit reform, the Annual Accounts Directive: 2013/34/EU, on firms and the society. Papers III, IV, and V examine firm behavior to assess the need for public regulation of nonfinancial reporting in the light of an EU-wide reform, the Nonfinancial Reporting Directive: 2014/95/EU, commonly known as the NFRD.The thesis posits that the current implementations of these reforms in some settings are imperfect and thus costly for the firms and society. It recommends deregulation of the monitoring of financial disclosure, i.e., to allow more small firms the option of deciding if an audit is beneficial for them or not. On the other hand, recommends a different approach for regulating nonfinancial reporting, e.g., sustainability reporting. For instance, regulations that can influence firms’ governance structure, e.g., board diversity. A firm with a diverse board is more likely to adopt a sustainability agenda which is better aligned with the expectations of the EU regulators. Stakeholders use firms’ disclosures to evaluate its performance and behavior for various decision making. For example, shareholders, in their investing or divesting decisions; analysts, in making various forecasts and recommendations; or governments, in assessing the need for reforms. Historically, stakeholders commonly used financial information for these types of decision making. Hence, there are well established generic measures to evaluate firms’ financial information (e.g., earnings quality measures and financial-statement ratios). Nowadays, stakeholders are increasingly using firms’ sustainability related information in their decision-making process as well. However, replicable and scalable generic measures to evaluate such information are missing. This thesis develops objective approaches and a generic measure, to evaluate firms’ sustainability related disclosures. The developed approaches for analyzing unstructured text data may be applied to other fields that can benefit from the use of natural language processing tools.
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| 17. |
- Huq, Asif M, et al.
(author)
-
Cyber Security Challenges and Opportunities in a Multi-Agent Environment : The case of Swedish Transport Administration
- 2022
-
Reports (other academic/artistic)abstract
- Cyberrisk utgör ett hot mot teknologier, data och individers och organisationers integritet. Svårigheten för organisationer i att skydda sig och reducera hoten har ökat som en följd av att cyberbrottslingar har tillgång till bättre metoder och verktyg för datastöld och systeminfiltration. Detta är i synnerhet sant vad gäller fleragentsystem där agenterna är digitalt sammanlänkade via Internet. Denna skrift rapporterar, med fokus på fleragentsystem, de vanligaste och mest fundamentala cyberhoten samt presenterar luckor och tillkortakommanden i utbudet av verktyg syftande till att reducera cyberhoten. Trafikverket och dess verksamhet ingår i fleragentssystem. Skriften redogör för de mest samtida problemen och möjligheterna relevanta för transportområdet. Vidare så pekar den ut framtida forskningsbehov syftande till att ge vägledning till dem som leder cyberförsvaret i transportområdet. Skriftens slutsatser vilar på en systematisk litteraturgenomgång av vetenskapliga arbeten.
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| 18. |
- Huq, Asif M
(author)
-
How does accounting and auditing regulations affect firm growth and cost of capital?
- 2018
-
Licentiate thesis (other academic/artistic)abstract
- This thesis provides an understanding of how new audit regulation affect firm growth and how audits affect the cost of capital. To investigate the effect of audit reforms on employment growth, we exploited a Swedish reform made in November 2010 that gave certain firms the option to opt out of previously imposed statutory audits. We find that firms which fulfilled the requirements for voluntary auditing, compared to a control group of similar firms that did not, increased their employment growth rate by 0.39%. Furthermore, the reform was also exploited to investigate if audited financial statements add value for firms in the private debt market. We find that firms with audited financial statements, on average, save 1.26 percentage points on cost of debt compared to firms with unaudited financial statements. Thus, the reform creates a possibility for firms that have the ambition to grow in employment to do so by not auditing, and those who want to grow by investments in capital to do so by reducing the cost of such investments by auditing. However, the current ceiling of the reform is also likely to force some firms to operate at sub-optimal levels, those without having the option to opt out of audit even though they might not accrue any benefit from auditing, at least in the short-run. One can argue that is partly due to how institutions evolve, generally slower than other actors in the society do.
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| 19. |
- Huq, Asif M, et al.
(author)
-
Measuring accountable information in CSR reports : A new operationalization and analysis applied to GHG disclosures
- 2020
-
Reports (other academic/artistic)abstract
- The paper contributes to the debate if voluntary nonfinancial disclosures, such as greenhouse gas disclosures in corporate social responsibility reporting, exhibit accountability or are merely greenwashing. If firms exhibit accountability, does their actions translate into observable impacts, e.g., as country-level real changes in GHG emissions? How do contextual factors affect accountable disclosures in CSR reporting? To answer these questions, we develop a novel measure to classify accountable information of GHG disclosures in CSR reporting. We operationalize the measure using natural language processing tools, such as collocation analysis, regular expressions, and text mining. Statistical models were used to carry out aggregate analysis to detect real effects in GHG emissions reductions and firm-level analysis to investigate how institutional factors affect accountable GHG disclosures. We find that firms headquartered or reporting in a civil-law legal-environment disclose significantly higher accountable information compared to those in a common-law legal-environment. However, there is a negative trend in accountability worldwide, and firm-level accountability in GHG disclosures is not detectable in a country-level reduction of GHG emissions. The results are robust for various alternative model specifications, and operationalization of the developed measure achieved high concordance when investigated on random samples manually. Compared to most past studies, we work with a significantly larger sample of 4459 reports across 82 countries, thereby dealing with greater complexity and leading to better generalizability. In addition, developing an approach that is many folds scalable and makes replicability straightforward. This is also one of the few studies to move beyond the usual “bag-of-words” approach in classifying voluminous corporate disclosure using NLP techniques.
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| 20. |
- Huq, Asif M, et al.
(author)
-
Measuring Accountable Information in CSR Reports: A New Operationalization and Analysis Applied to Greenhouse Gas Disclosures
- 2024
-
In: Journal of Emerging Technologies in Accounting. - : American Accounting Association. - 1554-1908 .- 1558-7940. ; 21:1, s. 59-88
-
Journal article (peer-reviewed)abstract
- We develop a novel and generic text-based measure to classify and evaluate greenhouse gas (GHG) disclosures. We construct the measure using collocation analysis of GHG-related words and regular expressions. Automated implementation achieved high concordance compared to manual investigations. We move beyond the “bag-of-words” approach in classifying voluminous nonfinancial corporate disclosure. We also outline a methodology that is manyfold scalable and makes replicability straightforward. Compared to past studies, we work with a significantly larger sample of 5,017 reports across 80 countries, thereby dealing with greater complexity and leading to better generalizability. We also contribute to the debate on whether nonfinancial disclosures exhibit accountability or are merely greenwashing. We find a negative trend in accountability worldwide, and firm-level accountability in GHG disclosures is not detectable in a country-level reduction of GHG emissions. Moreover, firms disclose significantly higher accountable information in a civil-law legal environment compared to those in a common-law legal environment.
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| 21. |
- Laryea, Rueben, 1977-
(author)
-
A data-driven decision support system for coherency of experts’ judgment in complex classification problems : The case of food security as a UN sustainable development goal
- 2018
-
Doctoral thesis (other academic/artistic)abstract
- Everyday humans need to make individual or collective decisions. Often the decisions aim at achieving multiple goals (thus involving multiple criteria) and rely on the decision maker(s)’ intuition, internal data, as well as external sources of data. Faced with a complex decision problem of this kind, it is a great challenge to decisionmakers to be logically coherent over time with regard to their preferences. To aid in achieving coherency, operation researchers and decision analysts have developed formal methods to support decision makers. One such method is the UTADIS method that serves as the workhorse for this thesis. I received the request from UN officials who had to manage the sustainable development goals while addressing the issue of food security. They wished for a decision support system (DSS) that could aid in their classification of countries to mitigate the risk of failing on food security. The virtue of the DSS should be that their expert judgment was complemented by formal methods for better risk classification. The UTADIS method was fitting for the purpose, but it lacked implementability. In particular, it required an iterative approach engaging the experts multiple times, while not readily lending itself to making use of external data, making it inefficient as a DSS. The fundamental contribution of this thesis is that I have solved these shortcomings of the UTADIS method, such that it now readily can be used in a functionally efficient way for the desired purpose of the UN. In solving these problems, it is also more broadly implementable as a DSS, as I have validated the artifact to a DSS, by use of several demonstrations and exposed it to sensitivity analysis.
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| 22. |
- Laryea, Rueben, 1977-, et al.
(author)
-
A decision support system that incorporates price volatility in risk classifying regional food security
- 2020
-
In: International Journal of Risk Assessment and Management. - 1466-8297 .- 1741-5241. ; 23:3/4, s. 223-235
-
Journal article (peer-reviewed)abstract
- Let us consider a cooperative group of decision-makers striving to strategise against failing to attain a goal. The risk of failure depends on external factors and the decision-makers' assessment and acceptance of risk. Furthermore, the setting is complex, e.g. owing to multiple objectives and criteria, making it difficult for the individual decision-maker, as well as the group, to assess the risk in a coherent way. To aid humans in this situation formal risk frameworks have been developed. One such framework is UTADIS (UTilities Additives DIScriminantes) and the contribution of this paper is to complement this framework with objective measures of volatility. This is done in such a way that the original features of UTADIS are preserved. This paper demonstrates how objective time-series data can be exploited in groups' risk mitigating for a given decision problem. To illustrate how this solution is implemented we consider the problem of United Nations policy-makers in monitoring food security as a UN sustainable development goal. The aim of the policy makers is to classify countries into crisis groups, giving due importance to the price volatility of food staples. UTADIS is hereby applied for the purpose of developing a food price volatility classification model to satisfy the preferences of the decision-makers. The enhanced UTADIS method provides both the global risk scores of the countries and the utility threshold. This is achieved in an efficient manner, meaning that a minimised misclassification between the decision-makers' preferred classification and their authentic classification is obtained in just one iteration. The resulting marginal utility function is consequently accurate enough and validated to satisfy the preferences of the United Nations decision-makers in the making of classification on future datasets.
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| 23. |
- Laryea, Rueben, 1977-, et al.
(author)
-
A Food Price Volatility Model for Country Risk Classification
- 2018
-
In: International Journal of Risk Assessment and Management. - 1466-8297 .- 1741-5241.
-
Journal article (peer-reviewed)abstract
- Decision makers require risk models which satisfies their preferences in decision making processes. A methodological approach to presenting a decision model that satisfies the preferences of the decision maker and aids the decision maker to classify countries into crisis groups based on the price volatility of food staple criteria is discussed in this paper. The price volatility of food staples is obtained from time series plots and a Multi-Criteria Decision Analysis method, the UTilitdditives DIScriminantes (UTADIS) classification methodological framework is applied on the price volatility data to develop a food price volatility classification model which suits the decision maker’s preferences. The methodological framework is better applied in this paper by aiding the decision maker to make informed judgements on the price volatility of food staples in predefining their risk classes. This introduces efficiency in the application of the methodological classification framework, by reducing to the barest minimum level, the misclassification errors between the decision makers preferred classification and the UTADIS method’s classification which estimates the utility function or classification model and the utility threshold or cut-off points which would classify the country alternatives into their authentic or original classes with the execution of the methodological framework just once. The resulting utility function or classification model is thus accurate enough to satisfy the preferences of the decision maker in classifying future datasets.
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| 24. |
- Laryea, Rueben, 1977-, et al.
(author)
-
Sensitivity analysis of a risk classification model for food price volatility
- 2018
-
In: International Journal of Risk Assessment and Management. - 1466-8297 .- 1741-5241. ; 21:4, s. 374-382
-
Journal article (peer-reviewed)abstract
- A sensitivity analysis to vary the weights of an accurate predictive classification model to produce a mixed model for ranking countries on the risk of food price volatility is carried out in this paper. The classification model is a marginal utility function consisting of multiple criteria. The aim of the sensitivity analysis is to derive a mixed model to be used in ranking of country alternatives to aid in policy formulation. Since in real-life situations the data that goes into decision making could be subjected to possibilities of alterations over time, it is essential to aid decision makers to vary the weights of the criteria using both subjective and objective information to introduce imprecision and to generate relative values of the criteria with a scale to form a mixed model. The mixed model can be used to rank future relative alternative value data sets for policy formulation.
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| 25. |
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| 26. |
- Lindgren, Charlie, et al.
(author)
-
Who are the intended users of CSR reports? : Insights from a data-driven approach
- 2021
-
In: Sustainability. - : MDPI AG. - 2071-1050. ; 13:3, s. 1070-1090
-
Journal article (peer-reviewed)abstract
- There is extant research on theorization, conceptualization, determinants, and consequences of corporate social responsibility (CSR). However, what firms include in their CSR or sustainability reports are much less covered and are predominantly covered in case studies of individual firms. In this paper, we instead take a holistic view and simultaneously explore what firms around the globe currently disclose in these reports, more specifically we investigate if firms are shareholder or stakeholder focused. In this investigation, we check the alignment of the reports to the materiality framework of Sustainability Accounting Standards Board (SASB) which was developed having shareholders as the intended user. To estimate what firms disclose in CSR reports we used the unsupervised Bayesian machine learning approach latent Dirichlet allocation (LDA) developed by Blei et al. We conclude that firms target shareholders as the intended users of these reports, even in environments where stakeholder approach of management is argued to be more dominant. Methodologically, we contribute by demonstrating that topic modeling can enhance the objectivity in reviewing CSR-reports.
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| 27. |
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| 28. |
- May, Ross
(author)
-
On the Feasibility of Reinforcement Learning in Single- and Multi-Agent Systems : The Cases of Indoor Climate and Prosumer Electricity Trading Communities
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Over half of the world’s population live in urban areas, a trend which is expected to only grow as we move further into the future. With this increasing trend in urbanisation, challenges are presented in the form of the management of urban infrastructure systems. As an essential infrastructure of any city, the energy system presents itself as one of the biggest challenges. Indeed, as cities expand in population and economically, global energy consumption increases, and as a result, so do greenhouse gas (GHG) emissions. Key to realising the goals as laid out by the 2030 Agenda for Sustainable Development, is the energy transition - embodied in the goals pertaining to affordable and clean energy, sustainable cities and communities, and climate action. Renewable energy systems (RESs) and energy efficiency have been shown as key strategies towards achieving these goals. While the building sector is considered to be one of the biggest contributors to climate change, it is also seen as an area with many opportunities for realising the energy transition. Indeed, the emergence of the smart city and the internet of things (IoT), alongside Photovoltaic and battery technology, offers opportunities for both the smart management of buildings, as well as the opportunity to form self-sufficient peer-to-peer (P2P) electricity trading communities. Within this context, advanced building control offers significant potential for mitigating global warming, grid instability, soaring energy costs, and exposure to poor indoor building climates. Most advanced control strategies, however, rely on complex mathematical models, which require a great deal of expertise to construct, thereby costing in time and money, and are unlikely to be frequently updated - which can lead to sub-optimal or even wrong performance. Furthermore, arriving at solutions in economic settings as complex and dynamic as the P2P electricity markets referred to above, often leads to solutions that are computationally intractable. A model-based approach thus seems, as alluded to above, unsustainable, and I thus propose taking a model-free alternative instead. One such alternative is the reinforcement learning (RL) method. This method provides a beautiful solution that addresses many of the limitations seen in more classical approaches - those based on complex mathematical models - to single- and multi-agent systems. To address the feasibility of RL in the context of building systems, I have developed four papers. In studying the literature, while there is much review work in support of RL for controlling energy consumption, it was found that there were no such works analysing RL from a methodological perspective w.r.t. controlling the comfort level of building occupants. Thus, in Paper I, to fill in this gap in knowledge, a comprehensive review in this area was carried out. To follow up, in Paper II, a case study was conducted to further assess, among other things, the computational feasibility of RL for controlling occupant comfort in a single agent context. It was found that the RL method was able to improve thermal and indoor air quality by more than 90% when compared with historically observed occupant data. Broadening the scope of RL, Papers III and IV considered the feasibility of RL at the district scale by considering the efficient trade of renewable electricity in a peer-to-peer prosumer energy market. In particular, in Paper III, by extending an open source economic simulation framework, multi-agent reinforcement learning (MARL) was used to optimise a dynamic price policy for trading the locally produced electricity. Compared with a benchmark fixed price signal, the dynamic price mechanism arrived at by RL, increased community net profit by more than 28%, and median community self-sufficiency by more than 2%. Furthermore, emergent social-economic behaviours such as changes in supply w.r.t changes in price were identified. A limitation of Paper III, however, is that it was conducted in a single environment. To address this limitation and to assess the general validity of the proposed MARL-solution, in Paper IV a full factorial experiment based on the factors of climate - manifested in heterogeneous demand/supply profiles and associated battery parameters, community scale, and price mechanism, was conducted in order to ascertain the response of the community w.r.t net-loss (financial gain), self-sufficiency, and income equality from trading locally produced electricity. The central finding of Paper IV was that the community, w.r.t net-loss, performs significantly better under a learned dynamic price mechanism than under the benchmark fixed price mechanism, and furthermore, a community under such a dynamic price mechanism stands an odds of 2 to 1 in increased financial savings.
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| 29. |
- May, Ross
(author)
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The reinforcement learning method : A feasible and sustainable control strategy for efficient occupant-centred building operation in smart cities
- 2019
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Licentiate thesis (other academic/artistic)abstract
- Over half of the world’s population lives in urban areas, a trend which is expected to only grow as we move further into the future. With this increasing trend in urbanisation, challenges are presented in the form of the management of urban infrastructure systems. As an essential infrastructure of any city, the energy system presents itself as one of the biggest challenges. As cities expand in population and economically, global energy consumption increases and as a result so do greenhouse gas (GHG) emissions. To achieve the 2030 Agenda’s sustainable development goal on energy (SDG 7), renewable energy and energy efficiency have been shown as key strategies for attaining SDG 7. As the largest contributor to climate change, the building sector is responsible for more than half of the global final energy consumption and GHG emissions. As people spend most of their time indoors, the demand for energy is made worse as a result of maintaining the comfort level of the indoor environment. However, the emergence of the smart city and the internet of things (IoT) offers the opportunity for the smart management of buildings. Focusing on the latter strategy towards attaining SDG 7, intelligent building control offers significant potential for saving energy while respecting occupant comfort (OC). Most intelligent control strategies, however, rely on complex mathematical models which require a great deal of expertise to construct thereby costing in time and money. Furthermore, if these are inaccurate then energy is wasted and the comfort of occupants is decreased. Moreover, any change in the physical environment such as retrofits result in obsolete models which must be re-identified to match the new state of the environment. This model-based approach seems unsustainable and so a new model-free alternative is proposed. One such alternative is the reinforcement learning (RL) method. This method provides a beautiful solution to accomplishing the tradeoff between energy efficiency and OC within the smart city and more importantly to achieving SDG 7. To address the feasibility of RL as a sustainable control strategy for efficient occupant-centred building operation, a comprehensive review of RL for controlling OC in buildings as well as a case study implementing RL for improving OC via a window system are presented. The outcomes of each seem to suggest RL as a feasible solution, however, more work is required in the form of addressing current open issues such as cooperative multi-agent RL (MARL) needed for multi-occupant/multi-zonal buildings.
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| 30. |
- Meng, Xiangli, et al.
(author)
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How do administrative borders affect accessibility to hospitals? The case of Sweden
- 2018
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In: International Journal of Health Planning and Management. - : Wiley. - 0749-6753 .- 1099-1751. ; 33:3
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Journal article (peer-reviewed)abstract
- An administrative border might hinder the optimal allocation of a given set of resources by restricting the flow of goods, services, and people. In this paper, we address the question: Do administrative borders lead to poor accessibility to public service? In answering the question, we have examined the case of Sweden and its regional administrative borders and hospital accessibility. We have used detailed data on the Swedish road network, its hospitals, and its geo-coded population. We have assessed the population's spatial accessibility to Swedish hospitals by computing the inhabitants' distance to the nearest hospital. We have also elaborated several scenarios ranging from strongly confining regional borders to no confinements of borders and recomputed the accessibility. Our findings imply that administrative borders are only marginally worsening the accessibility.
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| 31. |
- Meng, Xiangli, 1985-
(author)
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Optimization heuristic solutions, how good can they be? : With empirical applications in location problems
- 2015
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Doctoral thesis (other academic/artistic)abstract
- Combinatorial optimization problems, are one of the most important types of problems in operational research. Heuristic and metaheuristics algorithms are widely applied to find a good solution. However, a common problem is that these algorithms do not guarantee that the solution will coincide with the optimum and, hence, many solutions to real world OR-problems are afflicted with an uncertainty about the quality of the solution. The main aim of this thesis is to investigate the usability of statistical bounds to evaluate the quality of heuristic solutions applied to large combinatorial problems. The contributions of this thesis are both methodological and empirical. From a methodological point of view, the usefulness of statistical bounds on p-median problems is thoroughly investigated. The statistical bounds have good performance in providing informative quality assessment under appropriate parameter settings. Also, they outperform the commonly used Lagrangian bounds. It is demonstrated that the statistical bounds are shown to be comparable with the deterministic bounds in quadratic assignment problems. As to empirical research, environment pollution has become a worldwide problem, and transportation can cause a great amount of pollution. A new method for calculating and comparing the CO2-emissions of online and brick-and-mortar retailing is proposed. It leads to the conclusion that online retailing has significantly lesser CO2-emissions. Another problem is that the Swedish regional division is under revision and the border effect to public service accessibility is concerned of both residents and politicians. After analysis, it is shown that borders hinder the optimal location of public services and consequently the highest achievable economic and social utility may not be attained.
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| 32. |
- Rudholm, Niklas, et al.
(author)
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Gör internationella prisjämförelser handeln mera konjunkturkänslig?
- 2024
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Reports (other academic/artistic)abstract
- Syftet med vårt projekt har varit att studera hur en ökad internationalisering av handeln som bransch, med ökade internationella prisjämförelser och ökad internationell e-handel, påverkar e-handlares prissättning och lokala marknaders känslighet för asymmetriska chocker.
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| 33. |
- Rudholm, Niklas, et al.
(author)
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How Does Big-Box Entry Affect Labor Productivity in Durable Goods Retailing? A Synthetic Control Approach. How Does Big-Box Entry Affect Labor Productivity in Durable Goods Retailing? A Synthetic Control Approach
- 2018
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Reports (other academic/artistic)abstract
- Using data from 2001–2012, the effects of IKEA entry in four Swedish municipalities, 2004–2007, on labor productivity in durable goods retailing is investigated using synthetic control methods. We contribute to the literature on synthetic control methods by considering parametric specifications of the intervention effect, which in our case arguably improves the likelihood of identifying the intervention effect of IKEA entry on labor productivity. As inference relies on a single treated observational unit (i.e., a single IKEA-entry municipality), statistical testing is a challenge, and randomization and replication for inference is done with regard to the pool of control municipalities. Our results indicate that in three out of four entry municipalities, labor productivity increased more than in their synthetic counterparts after IKEA entry, and that the size of the positive effect is related to the size of the new IKEA relative to the size of the existing durable goods retail sector in the entry municipalities, with larger positive effects found in municipalities where the new IKEA was large relative to the existing durable goods retail market.
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| 34. |
- Rudholm, Niklas, et al.
(author)
-
How does Big-Box Retail Entry Affect Labor Productivity in Durable Goods Retailing? A Synthetic Control Approach
- 2022
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In: The annals of regional science. - : Springer Science and Business Media LLC. - 0570-1864 .- 1432-0592. ; 69:1, s. 89-117
-
Journal article (peer-reviewed)abstract
- Using data from 2001–2012, the effects of IKEA entry in four Swedish municipalities, 2004–2007, on labor productivity in durable goods retailing is investigated using synthetic control methods. We contribute to the literature on synthetic control methods by considering parametric specifications of the intervention effect, which improves the likelihood of identifying the effect of IKEA entry on labor productivity. Our results indicate that in three out of four entry municipalities, labor productivity increased more than in their synthetic counterparts after IKEA entry, and that larger positive effects are found in rural municipalities where the new IKEA was large relative to the existing durable goods retail market.
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| 35. |
- Sadeghian, Paria
(author)
-
Human mobility behavior : Transport mode detection by GPS data
- 2021
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Licentiate thesis (other academic/artistic)abstract
- GPS tracking data are widely used to understand human travel behavior and to evaluate the impact of travel. A major advantage with the usage of GPS tracking devices for collecting data is that it enables the researcher to collect large amounts of highly accurate and detailed human mobility data. However, unlabeled GPS tracking data does not easily lend itself to detecting transportation mode and this has given rise to a range of methods and algorithms for this purpose. The algorithms used vary in design and functionality, from defining specific rules to advanced machine learning algorithms. There is however no previous comprehensive review of these algorithms and this thesis aims to identify their essential features and methods and to develop and demonstrate a method for the detection of transport mode in GPS tracking data. To do this, it is necessary to have a detailed description of the particular journey undertaken by an individual. Therefore, as part of the investigation, a microdata analytic approach is applied to the problem areas, including the stages of data collection, data processing, analyzing the data, and decision making.In order to fill the research gap, Paper I consists of a systematic literature review of the methods and essential features used for detecting the transport mode in unlabeled GPS tracking data. Selected empirical studies were categorized into rule-based methods, statistical methods, and machine learning methods. The evaluation shows that machine learning algorithms are the most common. In the evaluation, I compared the methods previously used, extracted features, types of dataset, and model accuracy of transport mode detection. The results show that there is no standard method used in transport mode detection. In the light of these results, I propose in Paper II a stepwise methodology to detect five transport modes taking advantage of the unlabeled GPS data by first using an unsupervised algorithm to detect the five transport modes. A GIS multi-criteria process was applied to label part of the dataset. The performance of the five supervised algorithms was evaluated by applying them to different portions of the labeled dataset. The results show that stepwise methodology can achieve high accuracy in detecting the transport mode by labeling only 10% of the data from the entire dataset. For the future, one interesting area to explore would be the application of the stepwise methodology to a balanced and larger dataset. A semi-supervised deep-learning approach is suggested for development in transport mode detection, since this method can detect transport modes with only small amounts of labeled data. Thus, the stepwise methodology can be improved upon for further studies.
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| 36. |
- Zhao, Xiaoyun, Ph.D., et al.
(author)
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An evaluation of the reliability of GPS-based transportation data
- 2017
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In: Proceedings of IAC in Vienna 2017. - 9788088203049 ; , s. 323-334
-
Conference paper (peer-reviewed)abstract
- GPS-based data are becoming a cornerstone for real-time transportation applications. Tracking data of vehicles from GPS receivers are however susceptible to measurement errors. The assessment of the reliability of data from GPS receiver is a neglected issue, especially in a real road network setting and in the phase after data transfer but before information identification. An evaluation method is outlined and carried out by conducting a randomized experiment. We assess the reliability of GPS-based transportation data on geographical position, speed, and elevation from three varied receivers GlobalSat BT-338X, Magellan SporTrak Pro and smart phone for three transportation modes: bicycle, car, and bus. The positional error ranging from 0158 meters, and 74% to 100% with an error within 5 meters depending on the transportation mode and route, there is also a non-negligible risk for aberrant positioning. Speed is slightly underestimated or overestimated with errors around 5km/h except for SporTrak Pro which had an error of -10 km/h. Elevation measurements are unreliable with errors bigger than 100 meters.
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| 37. |
- Zhao, Xiaoyun
(author)
-
Government vs Market in Sustainable Residential Development? : Microdata analysis of car travel, CO2 emission and residence location
- 2017
-
Doctoral thesis (other academic/artistic)abstract
- Increasing car usage and travel demands between residential locations and destinations in order to fulfill the various needs of residents is a primary cause of CO2 emissions. To win the battle against climate change, a better understanding of the question relating to which urban residential form may most effectively mitigate the CO2 emissions is the key pathway.This dissertation is concerned with the above problem and it mainly considers three objectives in providing insights on answering the question. The first objective is to comprehensively and microscopically understand intra-urban car travel behavior. The second objective is to estimate the induced CO2 emissions from daily intra-urban car travel and to ex-ante evaluate residential plans. The third objective is to assess whether the governmental sustainable residential development objective is aligned with the objectives of the estate market actors. To explore the research questions related to the objectives, a microdata analysis process (data collection, data assessment and transformation, data storage, data analysis and decision-making) is applied and is found essential in gaining access to key variables in exploring the answer of a preferable urban form. The dissertation offers many new solutions to various technical aspects through a microdata analysis process.The primary contribution of this dissertation is that it outlines an operational model that comprehensively integrates the investors’ investment strategy, the residents’ choice behavior, and the governmental sustainability objective in the interest of making an ex-ante assessment of residential plans. This ex-ante assessment provides decision-support in sustainable residential development at foremost local level.The first finding from the implementation of the model on the case study is that the market actors’ objectives are, in general, aligned with the government’s sustainable residential development objective. The second finding indicates that re-shaping the urban form into a compact city is preferable in mitigating CO2 emissions, in spite of the fact that the case city is of a polycentric urban form. These findings provide support for those advocating the compact city as the ideal for sustainable residential development, and also provide foresight on settling the answer to the preferred re-shaping of urban forms in climate change.
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| 38. |
- Zhao, Xiaoyun, et al.
(author)
-
On assessing governmental sustainable residential planning and its alignment with residents’ and estate investors’ objectives
- 2017
-
Reports (other academic/artistic)abstract
- There are three key actors in forming the sustainable spatial distribution of residency in an area, (local) government, the estate investor and the resident, each with its own objective. Most urban planning studies have mainly focused on the ex-post evaluation of residential development by considering the objective of each actor separately. This paper outlines a conceptual model where the three key actors and their unique objectives are integrated with the aim of providing an ex-ante evaluation of residential development for government to make policies operational on a micro level. The methodology is implemented on a Swedish city, where sustainable residential development is in high need due to the influx of immigrants. The case study demonstrates that the model can integrate the macro and micro actors well. The model can provide noteworthy insights for the government on where the objectives of sustainability, livability and profit can be met. A sensitivity check of the parameter settings shows that the implementation of the model is robust for replication in other cities.
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| 39. |
- Zhao, Xiaoyun, et al.
(author)
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Residential planning, driver mobility and CO2 emission : a microscopic look at Borlänge in Sweden
- 2017
-
In: European Planning Studies. - : Informa UK Limited. - 0965-4313 .- 1469-5944. ; 25:9, s. 1597-1614
-
Journal article (peer-reviewed)abstract
- In a city there are hotspots that attract citizens, and most of the transportation arises when citizens move between their residence and primary destinations (i.e. hotspots). However, an ex ante evaluation of energy-efficient mobility and urban residential planning has seldom been conducted. Therefore, this paper proposes an ex ante evaluation method to quantify the impacts, in terms of CO2 emissions induced by intra-urban car mobility, of residential plans for various urban areas. The method is illustrated in a case study of a Swedish midsize city, which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. In general, CO2 emissions increase from the continued urban core area (CUCA), to the sub-polycentric area (SPA), to the edge urbanization area (EUA), where CO2 emission of EUA is twice that of the CUCA. The average travel distances also increase in the same pattern, though the relative increase is more than four times. Apartment buildings could be more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.
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| 40. |
- Zhao, Xiaoyun, Ph.D.
(author)
-
Road network and GPS tracking with data processing and quality assessment
- 2015
-
Licentiate thesis (other academic/artistic)abstract
- GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application.This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost.The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.
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