The effect of demand information sharing in a supply chain under demand uncertainty: a simulation study

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Asymmetric demand information in uniform and discriminatory call auctions: an experimental analysis motivated by electricity markets

We study the outcomes of experimental multi-unit uniform and discriminatory auctions with demand uncertainty. Our study is motivated by the ongoing debate about market design in the electricity industry. Our main aim is to compare the effect of asymmetric demand-information between sellers on the performance of the two auction institutions. In our baseline conditions all sellers have the same information, whereas in our treatment conditions some sellers have better information than others. In both information conditions we find that average transaction prices and price volatility are not significantly different under the two auction institutions. However, when there is asymmetric information among sellers the discriminatory auction is significantly less efficient. These results are not in line with the typical arguments made in favor of discriminatory pricing in electricity industries; namely, lower consumer prices and less price volatility. Moreover, our results provide some indication that discriminatory auctions reduce technical efficiency relative to uniform auctions.

Utah increases placements using current occupational data : [how current occupational supply and demand information can be used to increase local office placcements in Utah /

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Knowledge and information flows in supply chains: A study on pharmaceutical companies

A great deal of attention in the supply chain management literature is devoted to study material and demand information flows and their coordination. But in many situations, supply chains may convey information from different nature, they may be an important channel companies have to deliver knowledge, or specifically, technical information to the market. This paper studies the technical flow and highlights its particular requirements. Drawing upon a qualitative field research, it studies pharmaceutical companies, since those companies face a very specific challenge: consumers do not have discretion over their choices, ethical drugs must be prescribed by physicians to be bought and used by final consumers. Technical information flow is rich, and must be redundant and early delivered at multiple points. Thus, apart from the regular material channel where products and order information flow, those companies build a specialized information channel, developed to communicate to those who need it to create demand. Conclusions can be extended to supply chains where products and services are complex and decision makers must be clearly informed about technology-related information. (C) 2009 Elsevier B.V. All rights reserved.

Stackelberg leadership with demand uncertainty in a differentiated duopoly

On a symmetric differentiated Stackelberg duopoly model in which there is asymmetric demand information owned by leading and follower firms, we show that the leading firm does not necessarily have advantage over the following one. The reason for this is that the second mover can adjust its output level after observing the realized demand, while the first mover chooses its output level only with the knowledge of demand distribution.

Stackelberg duopoly with demand uncertainty

We consider a symmetric Stackelberg model in which there is asymmetric demand information owned by first and second movers. We analyse the advantages of leadership and flexibility, and prove that when the leading firm faces demand uncertainty, but the follower does not, the first mover does not necessarily have advantage over the second mover. Moreover, we show that the advantage of one firm over the other depends upon the demand fluctuation and also upon the degree of substitutability of the products.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Interfirm Information System for Supply Chain Management from the Cloud: An Exploratory Case Study from the Telecom Industry

This study examines the practice of supply chain management problems and the perceived demand information distortion’s (the bullwhip effect) reduction with the interfirm information system, which is delivered as a cloud service to a company operating in the telecommunications industry. The purpose is to shed light in practice that do the interfirm information system have impact on the performance of the supply chain and in particularly the reduction of bullwhip effect. In addition, a holistic case study of the global telecommunications company's supply chain is presented and also the challenges it’s facing, and this study also proposes some measures to improve the situation. The theoretical part consists of the supply chain and its management, as well as increasing the efficiency and introducing the theories and related previous research. In addition, study presents performance metrics for the bullwhip effect detection and tracking. The theoretical part ends in presenting cloud -based business intelligence theoretical framework used in the background of this study. The research strategy is a qualitative case study, supported by quantitative data, which is collected from a telecommunication sector company's databases. Qualitative data were gathered mainly with two open interviews and the e-mail exchange during the development project. In addition, other materials from the company were collected during the project and the company's web site information was also used as the source. The data was collected to a specific case study database in order to increase reliability. The results show that the bullwhip effect can be reduced with the interfirm information system and with the use of CPFR and S&OP models and in particularly combining them to an integrated business planning. According to this study the interfirm information system does not, however, solve all of the supply chain and their effectiveness -related problems, because also the company’s processes and human activities have a major impact.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.

Kuivatuotetoimitusketjun kehittäminen

Diplomityön tarkoituksena on selvittää kuivatuotetoimitusketjun haasteet ja kehittää toimintaan parannuskeinoja. Kuivatuotetoimitusketjun kehittämisessä pyritään varmistamaan tärkeimpien asiakkaiden tilauksien toimitusvarmuus sekä parantamaan asiakkailta saatavaa kysyntätietoa. Näistä kahdesta osa-alueesta muodostuu kokonaisuus, jonka avulla parannetaan toimitusketjun suorituskykyä. Työn tuloksena kysynnän ennustettavuutta kehitetään lähtötilanteesta toteutetulla kysyntäennustelomakkeella, jonka avulla kerätään tietoa tärkeimpien asiakkaiden tulevasta kysynnästä. Analyyseissä valmisvarastoille määritetään optimitasot, jolloin materiaalinohjausta voidaan hallita systemaattisemmin. Laskelmien yksityiskohtaisia tuloksia ei sisällytetä työhön. Työssä tarkastellaan myös varastotilan riittävyyttä sekä vaihtoehtoja kapasiteetin lisäämiseksi.

Käyttöpääoman sitoutuminen ja kiertoajat lääkejakeluketjussa

Työn tavoitteenaan oli selvittää suomalaisen lääkejakeluketjun rakenne sekä saada selkeä kuva ketjun toiminnan tehokkuudesta käyttöpääoman sitoutumisen ja kiertoaikojen osalta. Työn alussa käydään läpi teoriaa ja tutkimusta käyttöpääomasta ja sen erien kiertoajoista sekä erityisesti niiden huomioimisesta arvoketjussa. Lisäksi esitellään Suomen lääkemarkkinoiden toimintaa sekä sen toimijoita. Työn empiirinen osa suoritettiin kahdessa päävaiheessa. Ensin analysoitiin Voitto+ -ohjelmasta saatuja valittujen lääkejakeluketjun yritysten julkisia tilinpäätöstietoja ajalta 2005- 2011. Analysointi perustui käyttöpääoman sekä sen erien myyntisaamisten, ostovelkojen ja vaihto-omaisuuden kiertoaikojen laskemiseen. Ketjun yrityksiä vertailtiin toisiinsa ketjun osien keskimääräisten kiertoaikojen osalta ja saatiin selville niiden suhteellinen sijoittuminen toisiinsa nähden. Työn toisessa päävaiheessa haastateltiin esimerkkitoimijaa käsitellyn lääkejakeluketjun jokaisesta osasta: lääketehdas, tukkujakelija ja apteekki. Työssä huomattiin, että käyttöpääoman kiertoaikaan lääkejakeluketjussa vaikuttaa ensisijaisesti ketjun osan toiminnan luonne ja käyttöpääoman hallinnan tehokkuus lääkejakeluketjun toimijoiden välillä vaihtelee osaamisen ja resurssien mukaan. Ketjun eri osissa painottuvat eri käyttöpääoman erät ja ketjun toiminta on optimoitunut aikojen saatossa hyvin stabiiliin tilaan, jota ketjun jäsenillä ei näytä olevan halua muuttaa. Lääkejakeluketjun käyttöpääomaan hallintaa voitaisiin tehostaa varastonhallintaa parantamalla sekä informaation jakamisella saattamalla kysyntätiedot nopeammin koko ketjun tietoon.

Epäsuoran kysyntätiedon hyödyntäminen verkkokaupan tuotevalikoima- ja hinnoittelupäätöksissä

Tässä diplomityössä tutkitaan, miten verkkokaupan kävijävirran käyttäytymistä analysoimalla voidaan tehdä perusteltuja, tarkoituksenmukaisiin nimikkeisiin ja niiden parametreihin kohdistuvia päätöksiä tilanteessa, jossa laajamittaisemmat historiatiedot toteutuneesta myynnistä puuttuvat. Teoriakatsauksen perusteella muodostettiin ratkaisumalli, joka perustuu potentiaalisten kysyntäajurien muodostamiseen ja testaamiseen. Testisarjan perusteella valittavaa ajuria käytetään estimoimaan nimikkeiden kysyntää, jolloin sitä voidaan käyttää toteutuneen myynnin sijasta esimerkiksi Pareto-analyysissä. Näin huomio on mahdollista keskittää rajattuun määrään merkitykseltään suuria nimikkeitä ja niiden yksityiskohtaisiin parametreihin, joilla on merkitystä asiakkaan ostopäätöstilanteissa. Lisäksi voidaan tunnistaa nimikkeitä, joiden ongelmana on joko huono verkkonäkyvyys tai yhteensopimattomuus asiakastarpeiden kanssa. Ajurien testaamisperiaatteena käytetään kertymäfunktioiden yhdenmukaisuustarkastelua, joka rakentuu kolmesta peräkkäisestä vaiheesta; visuaalisesta tarkastelusta, kahden otoksen 2-suuntaisesta Kolmogorov-Smirnov-yhteensopivuustestistä ja Pearsonin korrelaatiotestistä. Mallia ja sen avulla tuotettua kysynnän ajuria testattiin veneilyalan kuluttaja-asiakkaille suunnatussa verkkokaupassa, jossa sillä tunnistettiin Pareto-jakauman alkupäästä runsaasti nimikkeitä, joiden parametreissa oli myynnin kannalta epäedullisia tekijöitä. Jakauman toisessa päässä tunnistettiin satoja nimikkeitä, joiden ongelmana on ilmeisesti joko huono verkkonäkyvyys tai nimikkeiden yhteensopimattomuus asiakastarpeiden kanssa.

Integração de modelos de localização a sistemas de informações geográficas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)