Forecast reconciliation : methods, structures, criteria, and a new approach with spatial data

This PhD dissertation is a collection of four papers that aim to explore, in the marketing field, the research on hierarchical and grouped time-series reconciliation approaches. Those approaches are necessary when different departments of an organization have different needs regarding forecast aggregations. This work focuses, besides reconciliation approaches, on time-series forecasting methods, and on the importance of geographical information to better forecast and plan marketing strategies. The first paper is theoretical and argues on the importance to marketing of having accurate forecasts. It explores the current state of marketing research on modelling in general, and on forecast specifically. It covers the classifications of methods, datasets explored on current research, the basic model studied, and existing gaps. The paper concludes that marketing focuses on explanation, living a gap on accuracy evidence and on the applicability of the models proposed. The second paper explores those gaps by applying two current topics of discussion on forecasting time-series literature: machine learning techniques and ensemble models. These methods are easy to implement and are reported in the literature to improve accuracy. The paper proposes an adaptation to portfolio optimization to calculate the weights of an ensemble based on each base model's accuracy and the covariance matrix of such accuracies. The proposed approach outperforms all 15 base models and the equal weights benchmark. The paper also provides evidence that, if single models are compared, statistical methods have better accuracy than the machine learning methods applied. The third paper uses a statistical method to forecast time-series (i.e. sales) combined with different structure and criteria of aggregation. The aim of the paper is to compare different criteria based on marketing mix variables. The empirical application presented in the paper indicates whether product category, channel type or region (geographic location) works best alone or combined. It also gives evidence of the importance of geographical considerations to improve forecast accuracy. The last paper furthers explore this finding by proposing a new reconciliation approach that distributes an aggregate forecast to lower levels of disaggregation using a gravitational model. This paper also contributes to the literature by comparing statistical, machine learning and deep learning methods (LSTM). All papers presented in this dissertation use open-source tools, combining proprietary data that is natural to the process of every organization and publicly available data. The focus is on methods and tools that are generalizable to all types of goods, can be easily applied by any organization, with relatively low investment. The contributions of the PhD dissertation are (1) to compare statistical, machine learning and deep learning methods to forecast sales on single and ensemble models; (2) to provide evidence on the criteria and structure of aggregation that improves forecast accuracy the most; and (3) to offer a new approach to distribute an aggregate forecast to new geographical regions when no historical data is available.A presente tese de doutorado é uma coleção de quatro artigos científicos desenvolvidos com o objetivo de explorar, dentro da área de marketing, a pesquisa sobre reconciliação de previsão de séries temporais com estrutura hierárquica ou agrupada. Reconciliação de previsões é necessária quando diferentes áreas de uma organização necessitam de previsões em diferentes níveis de agregação. O presente conjunto de estudos foca, além da reconciliação de previsões, em métodos de previsão de series temporais e na importância de informações geográficas para melhor prever e planejar estratégias de marketing. O primeiro artigo apresentado é uma revisão da literatura atual em modelagem de marketing, focando nos estudos sobre previsão. O artigo argumenta sobre a importância para o marketing em ter previsões, nas diferentes classificações dos métodos, nos tipos de dados usados, no modelo básico estudado e nos potenciais para estudos futuros. O artigo conclui que marketing precisa de estudos que evidenciem acurácia e sejam fáceis de implementar na prática. O segundo artigo procurar preencher essas lacunas aplicando técnicas de machine learning e ensemble. Essas técnicas são discutidas atualmente na teoria sobre previsão de séries temporais por prometerem facilidade de aplicação e melhoria em acurácia. O artigo propõe uma adaptação da otimização de portfólio como estratégia para calcular os pesos dos diferentes modelos que compõe um ensemble. A proposta do artigo tem melhor acurácia, no teste realizado, que os 15 modelos únicos (estatísticos e de machine learning) e o ensemble usando pesos iguais para todos os modelos. O artigo contribui também para a discussão sobre machine learning para previsão de séries temporais, demonstrando, nesse caso, a superioridade dos modelos estatísticos. O terceiro artigo usa um método estatístico combinado com diferentes estruturas e critérios de agregação para prever séries temporais (vendas). O objetivo do artigo é comparar diferentes critérios baseados em variáveis de marketing. A aplicação empírica dá indícios de que informações sobre a localização das vendas aumenta a acurácia das previsões. O último artigo explora esse achado ao propor uma estratégia alternativa de reconciliação de previsões. Essa estratégia distribui uma previsão feita em um nível agregado para níveis desagregados usando um modelo gravitacional. O artigo também contribui para a literatura ao comparar métodos estatísticos e de machine learning com long short-term memory (LSTM), um método de deep learning. Todos os artigos usam ferramentas open-source e combinam dados públicos com dados proprietários que resultam naturalmente dos processos de qualquer organização. O foco dos estudos são métodos e ferramentas generalizáveis para todos os segmentos que possam ser facilmente implementados por qualquer empresa, com relativamente baixos investimentos. As contribuições dessa tese de doutorado são (1) comparar métodos estatísticos, de machine learning e deep learning para prever vendas em modelos únicos e combinados (ensemble); (2) prover evidências sobre os critérios e estruturas de agregação que melhoram a acurácia das previsões; e (3) oferecer uma nova estratégia para distribuir uma previsão agregada em novas regiões geográficas quando dados históricos não estão disponíveis

Enhancement Motivation Derived from Envy: The Positive Influence of Watching Others Receive Preferential Treatment

As a strategy to build loyal relationships with highly profitable customers, the practice of customer prioritization has been widely adopted by a variety of firms in service industries. Although prior research has shown there is value creation in allocating more resources to prioritized customers, nonprioritized customers were found to respond negatively to this practice. Given that unhappy customers can be costly to a firm and that it is common for a firm to have some desirable customers who are not in the position of receiving preferential treatment, it is important to investigate how to encourage positive responses from nonprioritized customers. In the current research, I aim to address this issue by drawing on social comparison theory. In particular, I propose that in the case of watching other customers receive preferential treatment, customers are likely to feel the emotion of envy toward the preferentially treated customers. The revenge motivation resulting from this envy can drive the unfavorable response of negative word of mouth, whereas the self-enhancement motivation derived from the envy can bring about the favorable response of program participation. The boundary conditions of rule knowledge and attitudinal loyalty were identified. Two studies were conducted to examine the proposed research. The first study experimentally manipulated preferential treatment and knowledge of reward program rules using video-based scenarios (N = 303). The second study investigated the complete conceptual model with a field study of hotel customers (N = 529). Across the two studies, two double-mediation paths were confirmed, but a moderating effect of rule knowledge and attitudinal loyalty was not found. Follow-up analysis suggested the potential moderator role of rule appropriateness. The research contributes to a growing body of knowledge about envy, customer prioritization, and social comparison. It also provides recommendations for marketing practitioners with respect to managing customer prioritization practices to build long-term relationships with customers.Business Administratio

Ambiguity Aversion in the Front-End of Innovation

There have been repeated appeals for further scientific inquiry into the early stages of innovation in the firm, referred to as the front-end of innovation. Currently, we lack a clear understanding of front-end decision-making processes. Conceptually, the front-end stages of innovation are likely to include decisions involving ambiguity rather than risk. One way to view the innovation process is that considerable effort is expended on risk-reduction. That is to say, the innovation/new product development process converts amorphous ideas into tangible products that have a maximum chance of success in the commercial marketplace. However, this may lead to a preference for advancing product concepts where risk, in terms of clear probabilities, can be more easily established. At the same time, those new ideas and product concepts that are ambiguous may be discarded or screened out simply because it seems difficult to discover the probability estimates associated with their outcome success. This is ambiguity aversion, and it has been found to be an important predictor of decision making under uncertainty. Using a framework based on decision theory and the theory of expected utility, I propose and test a model in which ambiguity aversion has a detrimental effect on the performance of front-end innovation activities due to a suppression of decision-making comprehensiveness. Innovation culture and innovative capacity also play important roles in the success of front-end innovation activities. The data is collected from a sample of managers (N = 175) with active roles in innovation management. In summary, the results of a revised model serves to provide a valuable framework through which firms and managers can improve front-end of innovation performance. Multiple directions for future research are also discussed.Marketin

Disseny d'un model d'avaluació de resultats de l'activitat de màrqueting per a empreses competint al mercat català i amb relació contractual amb els seus clients

L’objectiu de la tesi doctoral és el de desenvolupar un model que permeti valorar de forma objectiva les actuacions en matèria de màrqueting portades a terme per una organització. Aquest model està constituït per un conjunt de variables descriptives i quantitatives, anomenades variables de control, juntament amb una metodologia de càlcul i un sistema d’indicadors integrat que facilita la traçabilitat de les inversions de màrqueting i explicita la relació causa-efecte entre aquestes i el valor generat per a l’organització. El model s’utilitza per a valorar dades reals d’organitzacions que operin al mercat català i que compleixin la condició de basar la relació amb els seus clients en un model contractual (com veurem més endavant, és inviable aplicar un model comú per a tot tipus d’empresa). L’objectiu, doncs, és la valoració de l’acompliment dels seus objectius en relació als seus actius de mercat (marca i valor de client) i la creació d’un model específic, no generalitzable, per a aquest tipus d’empreses. Un segon objectiu d’aquest treball és l’anàlisi de les principals publicacions especialitzades referents des d’un punt de vista global i local, proposant en primer lloc una terminologia clara en relació a l’activitat de màrqueting, l’acompliment dels seus objectius i la conceptualització d’actius de mercat, i analitzant, en segon, l’impacte d’aquests àmbits i la seva evolució en els últims quinze anys. Alguns estudis previs (Llonch et al., 2002; Ambler i Xiucun, 2003; entre d’altres) es centren a comparar empreses per sectors, funcionalitats i països. És probable, com apunta Llonch et al. (2002) al fer això, que casuístiques atribuïbles a diferències geogràfiques i nacionals es tractin erròniament com a empresarials. A tal efecte, aquest estudi elimina la variabilitat per país i sector (parcialment, aquest darrer), proposant un model acotat, tal com recomanen Ambler et al., (2001), Llonch et al (2002), entre d’altres, que pugui servir de referència en la metodologia i en la validesa conceptual, i no tant en els resultats del model en un context més genèric. Pauwels (2009) demostra la relació entre la creació d’un model predefinit de variables i la millora del càlcul de l’eficiència en la despesa en màrqueting, pel que la creació d’aquest model integrat té l’objectiu d’esdevenir una eina de Gestió del Rendiment Corporatiu (GRC, en endavant1) (Bauer, 2004) aplicada a la gestió de màrqueting i els seus actius. Aquesta particularització del GRC rep el nom de Gestió del Rendiment de Màrqueting (GRM, en endavant2) (Ambler, 2000) i el seu objectiu és el d’augmentar la usabilitat i faciliti la generació d’informació per a la presa de decisions de la línia directiva de les organitzacions. L’abast de la tesi és el de crear el model des d’una perspectiva d’avaluació de l’activitat de màrqueting per part de la línia directiva, i no pas el desenvolupament informàtic d’una eina de suport a la presa de decisions ja que això, com apunten diversos autors (Dover, 2004; Schiff, 2008) i es tractarà amb més profunditat en el capítol 5, implicaria un nivell de personalització per cada empresa que no és objectiu d’aquesta tesi.The thes is aims to develop a practical model to asses m arketing perform ance within an organization. The model is basically structured around control metrics both from a qualitative and quantitatve approach, together with an integrated system of key performance indicators that enables marketing accountability through different organisational divisions, thus stating a solid cause/effect relationship between marketing activities and the value created for the organisation. The aformentioned model is used to assess marketing activites for catalan com panies with a contract-based customer relationship. Final assessment includes also a dynamic valuation of the company's market as sets . A second objective of the thes is is to review the current state of the art of marketing assessment literature from specialized journals both from a global and a local pers pective, defining a comprehensive list of related terms about marketing performance measurement, market-asset description and valuation and an accurate analysis about its evolution throughout the last 15 years.Postprint (published version