Strategic decision making in international firms: effect of top management team internationalization on international strategic decision process

In this research project, I have integrated two research streams on international strategic decisions making in international firms: upper echelons or top management teams (TMT) internationalization research and international strategic decision making process research. Both research streams in international business literature have evolved independently, but there is a potential in combining these two streams of research. The first empirical paper “TMT internationalization and international strategic decision making process: a decision level analysis of rationality, speed, and performance” explores the influence of TMT internationalization on strategic decision rationality and speed and, subsequently, their effect on international strategic decision effectiveness (performance). The results show that the internationalization of TMT is positively related to decision effectiveness and this relationship is mediated by decision rationality while the hypotheses regarding the association between TMT internationalization and decision speed, and the mediating effect of speed were not supported. The second paper “TMT internationalization and international strategic decision rationality: the mediating role of international information” of my thesis is a simple but logical extension of first paper. The first paper showed that TMT Internationalization has a significant positive effect on international strategic decision rationality. The second paper explicitly showed that TMT internationalization affect on international strategic decision rationality comes from two sources: international experience (personal international knowledge and information) and international information collected from managerial international contacts. For this research project, I have collected data from international software firms in Pakistan. My research contributes to the literature on upper echelons theory and strategic decision making in context of international business and international firms by explicitly examining the link between TMT internationalization and characteristics of strategic decisions making process (i.e. rationality and speed) in international firms and their possible mediating effect on performance.

Customer Evolution in Sales Channel Migration

This research has been triggered by an emergent trend in customer behavior: customers have rapidly expanded their channel experiences and preferences beyond traditional channels (such as stores) and they expect the company with which they do business to have a presence on all these channels. This evidence has produced an increasing interest in multichannel customer behavior and it has motivated several researchers to study the customers’ channel choices dynamics in multichannel environment. We study how the consumer decision process for channel choice and response to marketing communications evolves for a cohort of new customers. We assume a newly acquired customer’s decisions are described by a “trial” model, but the customer’s choice process evolves to a “post-trial” model as the customer learns his or her preferences and becomes familiar with the firm’s marketing efforts. The trial and post-trial decision processes are each described by different multinomial logit choice models, and the evolution from the trial to post-trial model is determined by a customer-level geometric distribution that captures the time it takes for the customer to make the transition. We utilize data for a major retailer who sells in three channels – retail store, the Internet, and via catalog. The model is estimated using Bayesian methods that allow for cross-customer heterogeneity. This allows us to have distinct parameters estimates for a trial and an after trial stages and to estimate the quickness of this transit at the individual level. The results show for example that the customer decision process indeed does evolve over time. Customers differ in the duration of the trial period and marketing has a different impact on channel choice in the trial and post-trial stages. Furthermore, we show that some people switch channel decision processes while others don’t and we found that several factors have an impact on the probability to switch decision process. Insights from this study can help managers tailor their marketing communication strategy as customers gain channel choice experience. Managers may also have insights on the timing of the direct marketing communications. They can predict the duration of the trial phase at individual level detecting the customers with a quick, long or even absent trial phase. They can even predict if the customer will change or not his decision process over time, and they can influence the switching process using specific marketing tools

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Gli assetti proprietari e di controllo nell'agroalimentare italiano

The recent default of important Italian agri-business companies provides a challenging issue to be investigated through an appropriate scientific approach. The events involving CIRIO, FERRUZZI or PARMALAT rise an important research question: what are the determinants of performance for Italian companies in the Italian agri – food sector? My aim is not to investigate all the factors that are relevant in explaining performance. Performance depends on a wide set of political, social, economic variables that are strongly interconnected and that are often very difficult to express by formal or mathematical tools. Rather, in my thesis I mainly focus on those aspects that are strictly related to the governance and ownership structure of agri – food companies representing a strand of research that has been quite neglected by previous scholars. The conceptual framework from which I move to justify the existence of a relationship between the ownership structure of a company, governance and performance is the model set up by Airoldi and Zattoni (2005). In particular the authors investigate the existence of complex relationships arising within the company and between the company and the environment that can bring different strategies and performances. They do not try to find the “best” ownership structure, rather they outline what variables are connected and how they could vary endogenously within the whole economic system. In spite of the fact that the Airoldi and Zattoni’s model highlights the existence of a relationship between ownership and structure that is crucial for the set up of the thesis the authors fail to apply quantitative analyses in order to verify the magnitude, sign and the causal direction of the impact. In order to fill this gap we start from the literature trying to investigate the determinants of performance. Even in this strand of research studies analysing the relationship between different forms of ownership and performance are still lacking. In this thesis, after a brief description of the Italian agri – food sector and after an introduction including a short explanation of the definitions of performance and ownership structure, I implement a model in which the performance level (interpreted here as Return on Investments and Return on Sales) is related to variables that have been previously identified by the literature as important such as the financial variables (cash and leverage indices), the firm location (North Italy, Centre Italy, South Italy), the power concentration (lower than 25%, between 25% and 50% and between 50% and 100% of ownership control) and the specific agri – food sector (agriculture, food and beverage). Moreover we add a categorical variable representing different forms of ownership structure (public limited company, limited liability company, cooperative) that is the core of our study. All those variables are fully analysed by a preliminary descriptive analysis. As in many previous contributions we apply a panel least squares analysis for 199 Italian firms in the period 1998 – 2007 with data taken from the Bureau Van Dijck Dataset. We apply two different models in which the dependant variables are respectively the Return on Investments (ROI) and the Return on Sales (ROS) indicators. Not surprisingly we find that companies located in the North Italy representing the richest area in Italy perform better than the ones located in the Centre and South of Italy. In contrast with the Modigliani - Miller theorem financial variables could be significant and the specific sector within the agri – food market could play a relevant role. As the power concentration, we find that a strong property control (higher than 50%) or a fragmented concentration (lower than 25%) perform better. This result apparently could suggest that “hybrid” forms of concentrations could create bad functioning in the decision process. As our key variables representing the ownership structure we find that public limited companies and limited liability companies perform better than cooperatives. This is easily explainable by the fact that law establishes that cooperatives are less profit – oriented. Beyond cooperatives public limited companies perform better than limited liability companies and show a more stable path over time. Results are quite consistent when we consider both ROI and ROS as dependant variables. These results should not lead us to claim that public limited company is the “best” among all possible governance structures. First, every governance solution should be considered according to specific situations. Second more robustness analyses are needed to confirm our results. At this stage we deem these findings, the model set up and our approach represent original contributions that could stimulate fruitful future studies aimed at investigating the intriguing issue concerning the effect of ownership structure on the performance levels.

Networks, Uncertainty, Applications and a Crusade for Optimality

In this thesis we address a collection of Network Design problems which are strongly motivated by applications from Telecommunications, Logistics and Bioinformatics. In most cases we justify the need of taking into account uncertainty in some of the problem parameters, and different Robust optimization models are used to hedge against it. Mixed integer linear programming formulations along with sophisticated algorithmic frameworks are designed, implemented and rigorously assessed for the majority of the studied problems. The obtained results yield the following observations: (i) relevant real problems can be effectively represented as (discrete) optimization problems within the framework of network design; (ii) uncertainty can be appropriately incorporated into the decision process if a suitable robust optimization model is considered; (iii) optimal, or nearly optimal, solutions can be obtained for large instances if a tailored algorithm, that exploits the structure of the problem, is designed; (iv) a systematic and rigorous experimental analysis allows to understand both, the characteristics of the obtained (robust) solutions and the behavior of the proposed algorithm.