A method for decision making with the OWA operator

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

The development of decision limits for the GH-2000 detection methodology using additional insulin-like growth factor-I and amino-terminal pro-peptide of type III collagen assays.

The GH-2000 and GH-2004 projects have developed a method for detecting GH misuse based on measuring insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP). The objectives were to analyze more samples from elite athletes to improve the reliability of the decision limit estimates, to evaluate whether the existing decision limits needed revision, and to validate further non-radioisotopic assays for these markers. The study included 998 male and 931 female elite athletes. Blood samples were collected according to World Anti-Doping Agency (WADA) guidelines at various sporting events including the 2011 International Association of Athletics Federations (IAAF) World Athletics Championships in Daegu, South Korea. IGF-I was measured by the Immunotech A15729 IGF-I IRMA, the Immunodiagnostic Systems iSYS IGF-I assay and a recently developed mass spectrometry (LC-MS/MS) method. P-III-NP was measured by the Cisbio RIA-gnost P-III-P, Orion UniQ? PIIINP RIA and Siemens ADVIA Centaur P-III-NP assays. The GH-2000 score decision limits were developed using existing statistical techniques. Decision limits were determined using a specificity of 99.99% and an allowance for uncertainty because of the finite sample size. The revised Immunotech IGF-I - Orion P-III-NP assay combination decision limit did not change significantly following the addition of the new samples. The new decision limits are applied to currently available non-radioisotopic assays to measure IGF-I and P-III-NP in elite athletes, which should allow wider flexibility to implement the GH-2000 marker test for GH misuse while providing some resilience against manufacturer withdrawal or change of assays. Copyright © 2015 John Wiley & Sons, Ltd.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

Statistical Analysis of an SEIR Epidemic Model

This thesis was focussed on statistical analysis methods and proposes the use of Bayesian inference to extract information contained in experimental data by estimating Ebola model parameters. The model is a system of differential equations expressing the behavior and dynamics of Ebola. Two sets of data (onset and death data) were both used to estimate parameters, which has not been done by previous researchers in (Chowell, 2004). To be able to use both data, a new version of the model has been built. Model parameters have been estimated and then used to calculate the basic reproduction number and to study the disease-free equilibrium. Estimates of the parameters were useful to determine how well the model fits the data and how good estimates were, in terms of the information they provided about the possible relationship between variables. The solution showed that Ebola model fits the observed onset data at 98.95% and the observed death data at 93.6%. Since Bayesian inference can not be performed analytically, the Markov chain Monte Carlo approach has been used to generate samples from the posterior distribution over parameters. Samples have been used to check the accuracy of the model and other characteristics of the target posteriors.

Expertise and decision making among clinicians in investigations of alleged child sexual abuse

The purpose of the present thesis was to explore different aspects of decision making and expertise in investigations of child sexual abuse (CSA) and subsequently shed some light on the reasons for shortcomings in the investigation processes. Clinicians’ subjective attitudes as well as scientifically based knowledge concerning CSA, CSA investigation and interviewing were explored. Furthermore the clinicians’ own view on their expertise and what enhances this expertise was investigated. Also, the effects of scientific knowledge, experience and attitudes on the decision making in a case of CSA were explored. Finally, the effects of different kinds of feedback as well as experience on the ability to evaluate CSA in the light of children’s behavior and base rates were investigated. Both explorative and experimental methods were used. The purpose of Study I was to investigate whether clinicians investigating child sexual abuse (CSA) rely more on scientific knowledge or on clinical experience when evaluating their own expertise. Another goal was to check what kind of beliefs the clinicians held. The connections between these different factors were investigated. A questionnaire covering items concerning demographic data, experience, knowledge about CSA, selfevaluated expertise and beliefs about CSA was given to social workers, child psychiatrists and psychologists working with children. The results showed that the clinicians relied more on their clinical experience than on scientific knowledge when evaluating their expertise as investigators of CSA. Furthermore, social workers possessed stronger attitudes in favor of children than the other groups, while child psychiatrists had more negative attitudes towards the criminal justice system. Male participants held less strong beliefs than female participants. The findings indicate that the education of CSA investigators should focus more on theoretical knowledge and decision making processes as well as the role of beliefs In Study II school and family counseling psychologists completed a Child Sexual Abuse Attitude and Belief Scale. Four CSA related attitude and belief subscales were identified: 1. The Disclosure subscale reflecting favoring a disclosure at any cost, 2. The Pro-Child subscale reflecting unconditional belief in children's reports, 3. The Intuition subscale reflecting favoring an intuitive approach to CSA investigations, and 4. The Anti Criminal Justice System subscale reflecting negative attitudes towards the legal system. Beliefs that were erroneous according to empirical research were analyzed separately. The results suggest that some psychologists hold extreme attitudes and many erroneous beliefs related to CSA. Some misconceptions are common. Female participants tended to hold stronger attitudes than male participants. The more training in interviewing children the participants have, the more erroneous beliefs and stronger attitudes they hold. Experience did not affect attitudes and beliefs. In Study III mental health professionals’ sensitivity to suggestive interviewing in CSA cases was explored. Furthermore, the effects of attitudes and beliefs related to CSA and experience with CSA investigations on the sensitivity to suggestive influences in the interview were investigated. Also, the effect of base rate estimates of CSA on decisions was examined. A questionnaire covering items concerning demographic data, different aspects of clinical experience, self-evaluated expertise, beliefs and knowledge about CSA and a set of ambiguous material based on real trial documents concerning an alleged CSA case was given to child mental health professionals. The experiment was based on a 2 x 2 x 2 x 2 (leading questions: yes vs no) x (stereotype induction: yes vs no) x (emotional tone: pressure to respond vs no pressure to respond) x (threats and rewards: yes vs no) between-subjects factorial design, in which the suggestiveness of the methods with which the responses of the child were obtained were varied. There was an additional condition in which the material did not contain any interview transcripts. The results showed that clinicians are sensitive only to the presence of leading questions but not to the presence of other suggestive techniques. Furthermore, the clinicians were not sensitive to the possibility that suggestive techniques could have been used when no interview transcripts had been included in the trial material. Experience had an effect on the sensitivity of the clinicians only regarding leading questions. Strong beliefs related to CSA lessened the sensitivity to leading questions. Those showing strong beliefs on the belief scales used in this study were even more prone to prosecute than other participants when other suggestive influences than leading questions were present. Controversy exists regarding effects of experience and feedback on clinical decision making. In Study IV the impact of the number of handled cases and of feedback on the decisions in cases of alleged CSA was investigated. One-hundred vignettes describing cases of suspected CSA were given to students with no experience with investigating CSA. The vignettes were based on statistical data about symptoms and prevalence of CSA. According to the theoretical likelihood of CSA the children described were categorized as abused or not abused. The participants were asked to decide whether abuse had occurred. They were divided into 4 groups: one received feedback on whether their decision was right or wrong, one received information about cognitive processes involved in decision making, one received both, and one did not receive feedback at all. The results showed that participants who received feedback on their performance made more correct positive decisions and participants who got information about decision making processes made more correct negative decisions. Feedback and information combined decreased the number of correct positive decisions but increased the number of correct negative decisions. The number of read cases had in itself a positive effect on correct positive decision.

Role of references in international industrial marketing : a theory-building case study about supplier’s processes of utilizing references

Scientific studies regarding specifically references do not seem to exist. However, the utilization of references is an important practice for many companies involved in industrial marketing. The purpose of the study is to increase the understanding about the utilization of references in international industrial marketing in order to contribute to the development of a theory of reference behavior. Specifically, the modes of reference usage in industry, the factors affecting a supplier's reference behavior, and the question how references are actually utilized, are explored in the study. Due to the explorative nature of the study, a research design was followed where theory and empirical studies alternated. An Exploratory Framework was developed to guide a pilot case study that resulted in Framework 1. Results of the pilot study guided an expanded literature review that was used to develop first a Structural Framework and a Process Framework which were combined in Framework 2. Then, the second empirical phase of the case study was conducted in the same (pilot) case company. In this phase, Decision Systems Analysis (DSA) was used as the analysis method. The DSA procedure consists of three interviewing waves: initial interviews, reinterviews, and validating interviews. Four reference decision processes were identified, described and analyzed in the form of flowchart descriptions. The flowchart descriptions were used to explore new constructs and to develop new propositions to develop Framework 2 further. The quality of the study was ascertained by many actions in both empirical parts of the study. The construct validity of the study was ascertained by using multiple sources of evidence and by asking the key informant to review the pilot case report. The DSA method itself includes procedures assuring validity. Because of the choice to conduct a single case study, external validity was not even pursued. High reliability was pursued through detailed documentation and thorough reporting of evidence. It was concluded that the core of the concept of reference is a customer relationship regardless of the concrete forms a reference might take in its utilization. Depending on various contingencies, references might have various tasks inside the four roles of increasing 1) efficiency of sales and sales management, 2) efficiency of the business, 3) effectiveness of marketing activities, and 4) effectiveness in establishing, maintaining and enhancing customer relationships. Thus, references have not only external but internal tasks as well. A supplier's reference behavior might be affected by many hierarchical conditions. Additionally, the empirical study showed that the supplier can utilize its references as a continuous, all pervasive decision making process through various practices. The process includes both individual and unstructured decision making subprocesses. The proposed concept of reference can be used to guide a reference policy recommendable for companies for which the utilization of references is important. The significance of the study is threefold: proposing the concept of reference, developing a framework of a supplier's reference behavior and its short term process of utilizing references, and conceptual structuring of an unstructured and in industrial marketing important phenomenon to four roles.

Statistical Analysis and Numerics of Heat Exchanger Models

The identifiability of the parameters of a heat exchanger model without phase change was studied in this Master’s thesis using synthetically made data. A fast, two-step Markov chain Monte Carlo method (MCMC) was tested with a couple of case studies and a heat exchanger model. The two-step MCMC-method worked well and decreased the computation time compared to the traditional MCMC-method. The effect of measurement accuracy of certain control variables to the identifiability of parameters was also studied. The accuracy used did not seem to have a remarkable effect to the identifiability of parameters. The use of the posterior distribution of parameters in different heat exchanger geometries was studied. It would be computationally most efficient to use the same posterior distribution among different geometries in the optimisation of heat exchanger networks. According to the results, this was possible in the case when the frontal surface areas were the same among different geometries. In the other cases the same posterior distribution can be used for optimisation too, but that will give a wider predictive distribution as a result. For condensing surface heat exchangers the numerical stability of the simulation model was studied. As a result, a stable algorithm was developed.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

The effect of environmentally differentiated port fees to shipping companies’ environmental investments

The pressure has grown to develop cost-effective emission reduction strategies in the Baltic Sea. The forthcoming stringent regulations of the International Maritime Organization for reducing harmful emissions of shipping in the Baltic Sea are causing increasing expenses for the operators. A market-based attitude towards pricing of economic incentives could be seen as a new approach for a successful application for the additional emission reduction of nitrogen oxides (NOx). In this study the aim is to understand the phenomenon of environmentally differentiated port fees and its effects on shipping companies’ emission reduction investments. The goal is to examine empirically the real-life effects of the possible environmental differentiated port fee system and the effect of environmentally differentiated port fees on NOx reduction investments in the Baltic Sea. The research approach of this study is nomothetical. In this study research questions are answered by analyzing the broad database of the Baltic Sea fleet. Also the framework of theory is confirmed and plays an important role in analyzing the research problem. Existing investment costs of NOx emission reduction technology to ship owners are estimated and compared to investment costs with granted discounts added to the cash flows. The statistical analysis in this study is descriptive. The major statistic examination of this study is the calculation of the net present values of investments with different port fee scenarios. This is done to investigate if the NOx technology investments could be economically reasonable. Based on calculations it is clear that the effect of environmentally differentiated port fees is not adequate to compensate the total investment costs for NOx reduction. If the investment decision is made only with profitability considerations, sources will prefer to emission abatement as long as incomes from the given subsidy exceeds their abatement costs. Despite of the results, evidence was found that shipping companies are nevertheless willing to invest on voluntary emission abatement technology. In that case, investment decision could be made with criteria of, for example, sustainable strategy or brand image. Combined fairway and port fee system or governmental regulations and recommendation could also function as additional incentives to compensate the investment costs. Also, the results imply that the use of NPV is not necessarily the best method to evaluate environmental investments. If the calculations would be done with more environmental methods the results would probably be different.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Towards a contextual understanding of B2B salespeople's selling competencies – An exploratory study among purchasing decision-makers of internationally-oriented technology firms

ABSTRACT Towards a contextual understanding of B2B salespeople’s selling competencies − an exploratory study among purchasing decision-makers of internationally-oriented technology firms The characteristics of modern selling can be classified as follows: customer retention and loyalty targets, database and knowledge management, customer relationship management, marketing activities, problem solving and system selling, and satisfying needs and creating value. For salespeople to be successful in this environment, they need a wide range of competencies. Salespeople’s selling skills are well documented in seller side literature through quantitative methods, but the knowledge, skills and competencies from the buyer’s perspective are under-researched. The existing research on selling competencies should be broadened and updated through a qualitative research perspective due to the dynamic nature and the contextual dependence of selling competencies. The purpose of the study is to increase understanding of the professional salesperson’s selling competencies from the industrial purchasing decision- makers’ viewpoint within the relationship selling context. In this study, competencies are defined as sales-related knowledge and skills. The scope of the study includes goods, materials and services managed by a company’s purchasing function and used by an organization on a daily basis. The abductive approach and ‘systematic combining’ have been applied as a research strategy. In this research, data were generated through semi- structured, person-to-person interviews and open-ended questions. The study was conducted among purchasing decision-makers in the technology industry in Finland. The branches consisted of the electronics and electro-technical industries and the mechanical engineering and metals industries. A total of 30 companies and one purchasing decision-maker from each company were purposively chosen for the sampling. The sample covers different company sizes based on their revenues, their differing structures – varying from public to family companies –that represent domestic and international ownerships. Before analyzing the data, they were organized by the purchasing orientations of the buyers: the buying, procurement or supply management orientation. Thematic analysis was chosen as the analysis method. After analyzing the data, the results were contrasted with the theory. There was a continuous interaction between the empirical data and the theory. Based on the findings, a total of 19 major knowledge and skills were identified from the buyers’ perspective. The specific knowledge and skills from the viewpoint of customers’ prevalent purchasing orientations were divided into two categories, generic and contextual. The generic knowledge and skills apply to all purchasing orientations, and the contextual knowledge and skills depend on customers’ prevalent purchasing orientations. Generic knowledge and skills relate to price setting, negotiation, communication and interaction skills, while contextual ones relate to knowledge brokering, ability to present solutions and relationship skills. Buying-oriented buyers value salespeople who are ‘action oriented experts, however at a bit of an arm’s length’, procurement buyers value salespeople who are ‘experts deeply dedicated to the customer and fostering the relationship’ and supply management buyers value salespeople who are ‘corporate-oriented experts’. In addition, the buyer’s perceptions on knowledge and selling skills differ from the seller’s ones. The buyer side emphasizes managing the subject matter, consisting of the expertise, understanding the customers’ business and needs, creating a customized solution and creating value, reliability and an ability to build long-term relationships, while the seller side emphasizes communica- tion, interaction and salesmanship skills. The study integrates the selling skills of the current three-component model− technical knowledge, salesmanship skills, interpersonal skills− and relationship skills and purchasing orientations, into a selling competency model. The findings deepen and update the content of these knowledges and skills in the B2B setting and create new insights into them from the buyer’s perspective, and thus the study increases contextual understanding of selling competencies. It generates new knowledge of the salesperson’s competencies for the relationship selling and personal selling and sales management literature. It also adds knowledge of the buying orientations to the buying behavior literature. The findings challenge sales management to perceive salespeople’s selling skills both from a contingency and competence perspective. The study has several managerial implications: it increases understanding of what the critical selling knowledge and skills from the buyer’s point of view are, understanding of how salespeople effectively implement the relationship marketing concept, sales management’s knowledge of how to manage the sales process more effectively and efficiently, and the knowledge of how sales management should develop a salesperson’s selling competencies when managing and developing the sales force. Keywords: selling competencies, knowledge, selling skills, relationship skills, purchasing orientations, B2B selling, abductive approach, technology firms

Public-private partnership investments in dry ports – Russian logistics markets and risks

The investments have always been considered as an essential backbone and so-called ‘locomotive’ for the competitive economies. However, in various countries, the state has been put under tight budget constraints for the investments in capital intensive projects. In response to this situation, the cooperation between public and private sector has grown based on public-private mechanism. The promotion of favorable arrangement for collaboration between public and private sectors for the provision of policies, services, and infrastructure in Russia can help to address the problems of dry ports development that neither municipalities nor the private sector can solve alone. Especially, the stimulation of public-private collaboration is significant under the exposure to externalities that affect the magnitude of the risks during all phases of project realization. In these circumstances, the risk in the projects also is becoming increasingly a part of joint research and risk management practice, which is viewed as a key approach, aiming to take active actions on existing global and specific factors of uncertainties. Meanwhile, a relatively little progress has been made on the inclusion of the resilience aspects into the planning process of a dry ports construction that would instruct the capacity planner, on how to mitigate the occurrence of disruptions that may lead to million dollars of losses due to the deviation of the future cash flows from the expected financial flows on the project. The current experience shows that the existing methodological base is developed fragmentary within separate steps of supply chain risk management (SCRM) processes: risk identification, risk evaluation, risk mitigation, risk monitoring and control phases. The lack of the systematic approach hinders the solution of the problem of risk management processes of dry port implementation. Therefore, management of various risks during the investments phases of dry port projects still presents a considerable challenge from the practical and theoretical points of view. In this regard, the given research became a logical continuation of fundamental research, existing in the financial models and theories (e.g., capital asset pricing model and real option theory), as well as provided a complementation for the portfolio theory. The goal of the current study is in the design of methods and models for the facilitation of dry port implementation through the mechanism of public-private partnership on the national market that implies the necessity to mitigate, first and foremost, the shortage of the investments and consequences of risks. The problem of the research was formulated on the ground of the identified contradictions. They rose as a continuation of the trade-off between the opportunities that the investors can gain from the development of terminal business in Russia (i.e. dry port implementation) and risks. As a rule, the higher the investment risk, the greater should be their expected return. However, investors have a different tolerance for the risks. That is why it would be advisable to find an optimum investment. In the given study, the optimum relates to the search for the efficient portfolio, which can provide satisfaction to the investor, depending on its degree of risk aversion. There are many theories and methods in finance, concerning investment choices. Nevertheless, the appropriateness and effectiveness of particular methods should be considered with the allowance of the specifics of the investment projects. For example, the investments in dry ports imply not only the lump sum of financial inflows, but also the long-term payback periods. As a result, capital intensity and longevity of their construction determine the necessity from investors to ensure the return on investment (profitability), along with the rapid return on investment (liquidity), without precluding the fact that the stochastic nature of the project environment is hardly described by the formula-based approach. The current theoretical base for the economic appraisals of the dry port projects more often perceives net present value (NPV) as a technique superior to other decision-making criteria. For example, the portfolio theory, which considers different risk preference of an investor and structures of utility, defines net present value as a better criterion of project appraisal than discounted payback period (DPP). Meanwhile, in business practice, the DPP is more popular. Knowing that the NPV is based on the assumptions of certainty of project life, it cannot be an accurate appraisal approach alone to determine whether or not the project should be accepted for the approval in the environment that is not without of uncertainties. In order to reflect the period or the project’s useful life that is exposed to risks due to changes in political, operational, and financial factors, the second capital budgeting criterion – discounted payback period is profoundly important, particularly for the Russian environment. Those statements represent contradictions that exist in the theory and practice of the applied science. Therefore, it would be desirable to relax the assumptions of portfolio theory and regard DPP as not fewer relevant appraisal approach for the assessment of the investment and risk measure. At the same time, the rationality of the use of both project performance criteria depends on the methods and models, with the help of which these appraisal approaches are calculated in feasibility studies. The deterministic methods cannot ensure the required precision of the results, while the stochastic models guarantee the sufficient level of the accuracy and reliability of the obtained results, providing that the risks are properly identified, evaluated, and mitigated. Otherwise, the project performance indicators may not be confirmed during the phase of project realization. For instance, the economic and political instability can result in the undoing of hard-earned gains, leading to the need for the attraction of the additional finances for the project. The sources of the alternative investments, as well as supportive mitigation strategies, can be studied during the initial phases of project development. During this period, the effectiveness of the investments undertakings can also be improved by the inclusion of the various investors, e.g. Russian Railways’ enterprises and other private companies in the dry port projects. However, the evaluation of the effectiveness of the participation of different investors in the project lack the methods and models that would permit doing the particular feasibility study, foreseeing the quantitative characteristics of risks and their mitigation strategies, which can meet the tolerance of the investors to the risks. For this reason, the research proposes a combination of Monte Carlo method, discounted cash flow technique, the theory of real options, and portfolio theory via a system dynamics simulation approach. The use of this methodology allows for comprehensive risk management process of dry port development to cover all aspects of risk identification, risk evaluation, risk mitigation, risk monitoring, and control phases. A designed system dynamics model can be recommended for the decision-makers on the dry port projects that are financed via a public-private partnership. It permits investors to make a decision appraisal based on random variables of net present value and discounted payback period, depending on different risks factors, e.g. revenue risks, land acquisition risks, traffic volume risks, construction hazards, and political risks. In this case, the statistical mean is used for the explication of the expected value of the DPP and NPV; the standard deviation is proposed as a characteristic of risks, while the elasticity coefficient is applied for rating of risks. Additionally, the risk of failure of project investments and guaranteed recoupment of capital investment can be considered with the help of the model. On the whole, the application of these modern methods of simulation creates preconditions for the controlling of the process of dry port development, i.e. making managerial changes and identifying the most stable parameters that contribute to the optimal alternative scenarios of the project realization in the uncertain environment. System dynamics model allows analyzing the interactions in the most complex mechanism of risk management process of the dry ports development and making proposals for the improvement of the effectiveness of the investments via an estimation of different risk management strategies. For the comparison and ranking of these alternatives in their order of preference to the investor, the proposed indicators of the efficiency of the investments, concerning the NPV, DPP, and coefficient of variation, can be used. Thus, rational investors, who averse to taking increased risks unless they are compensated by the commensurate increase in the expected utility of a risky prospect of dry port development, can be guided by the deduced marginal utility of investments. It is computed on the ground of the results from the system dynamics model. In conclusion, the outlined theoretical and practical implications for the management of risks, which are the key characteristics of public-private partnerships, can help analysts and planning managers in budget decision-making, substantially alleviating the effect from various risks and avoiding unnecessary cost overruns in dry port projects.