Actively crafting customer value or merely representing a solution? Linking value-based selling to salesperson performance

Value-based selling is a salesperson behavioral mode which concentrates on generating superior customer value. Although service dominant logic emphasizes customer value as a central tenet for achieving strategic objectives, sales management literature has predominantly circumvented the subject matter of customer value. The purpose of this thesis is to demonstrate the distinctiveness and positive sales performance outcomes of value-based selling. Additionally, performance outcomes of value-based selling are contrasted with other key sales behaviors, selling skills and motivational orientations. As a part of this thesis, large-scale survey of 730 respondents was collected. The survey was tailored for the needs of a value-based selling research group led by Ph.D. Harri Terho. The research group used convenience sampling to select the salespeople of 25 medium- and large-scale companies in Finland which currently either practice value-based selling or consider developing these activities. This thesis contains three key findings: value-based selling is established as a distinct sales behavior, it relates directly and positively to salesperson performance and it explains the link between customer-oriented selling and salesperson performance. Value-based selling relates to salesperson performance especially in the following GICS-sectors: energy, industrials and materials. However, relationship selling relates to performance strongest in the energy sector and adaptive selling in industrials sector. In sum, it is evident that actively crafting customer value is a successful sales behavior in many business-to-business marketing environments while other sales behaviors, excluding customer-oriented selling, still uphold their significance.

Strategic management of value networks: how to create value in cross-sector collaboration and partnerships

Cross-sector collaboration and partnerships have become an emerging and desired strategy in addressing huge social and environmental challenges. Despite its popularity, cross-sector collaboration management has proven to be very challenging. Even though cross-sector collaboration and partnership management have been widely studied and discussed in recent years, their effectiveness as well as their ability to create value with respect to the problems they address has remained very challenging. There is little or no evidence of their ability to create value. Regarding all these challenges, this study aims to explore how to manage cross-sector collaborations and partnerships to be able to improve their effectiveness and to create more value for all partners involved in collaboration as well as for customers. The thesis is divided into two parts. The first part comprises an overview of relevant literature (including strategic management, value networks and value creation theories), followed by presenting the results of the whole thesis and the contribution made by the study. The second part consists of six research publications, including both quantitative and qualitative studies. The chosen research strategy is triangulation, as the study includes four types of triangulation: (1) theoretical triangulation, (2) methodological triangulation, (3) data triangulation and (4) researcher triangulation. Two publications represent conceptual development, which are based on secondary data research. One publication is a quantitative study, carried out through a survey. The other three publications represent qualitative studies, based on case studies, where data was collected through interviews and workshops, with participation of managers from all three sectors: public, private and the third (nonprofit). The study consolidates the field of “strategic management of value networks,” which is proposed to be applied in the context of cross-sector collaboration and partnerships, with the aim of increasing their effectiveness and the process of value creation. Furthermore, the study proposes a first definition for the strategic management of value networks. The study also proposes and develops two strategy tools that are recommended to be used for the strategic management of value networks in cross-sector collaboration and partnerships. Taking a step forward, the study implements the strategy tools in practice, aiming to show and to demonstrate how new value can be created by using the developed strategy tools for the strategic management of value networks. This study makes four main contributions. (1) First, it brings a theoretical contribution by providing new insights and consolidating the field of strategic management of value networks, also proposing a first definition for the strategic management of value networks. (2) Second, the study makes a methodical contribution by proposing and developing two strategy tools for value networks of cross-sector collaboration: (a) value network mapping, a method that allows us to assess the current and the potential value network and (b) the Value Network Scorecard, a method of performance measurement and performance prediction in cross-sector collaboration. (3) Third, the study has managerial implications, offering new solutions and empirical evidence on how to increase the effectiveness of cross-sector collaboration and also allow managers to understand how new value can be created in cross-sector partnerships and how to get the full potential of collaboration. (4) And fourth, the study also has practical implications, allowing managers to understand how to use in practice the strategy tools developed in this study, providing discussions on the limitations regarding the proposed tools as well as general limitations involved in the study.

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

Measuring Value in Product Development

“What is value in product development?” is the key question of this paper. The answer is critical to the creation of lean in product development. By knowing how much value is added by product development (PD) activities, decisions can be more rationally made about how to allocate resources, such as time and money. In order to apply the principles of Lean Thinking and remove waste from the product development system, value must be precisely defined. Unfortunately, value is a complex entity that is composed of many dimensions and has thus far eluded definition on a local level. For this reason, research has been initiated on “Measuring Value in Product Development.” This paper serves as an introduction to this research. It presents the current understanding of value in PD, the critical questions involved, and a specific research design to guide the development of a methodology for measuring value. Work in PD value currently focuses on either high-level perspectives on value, or detailed looks at the attributes that value might have locally in the PD process. Models that attempt to capture value in PD are reviewed. These methods, however, do not capture the depth necessary to allow for application. A methodology is needed to evaluate activities on a local level to determine the amount of value they add and their sensitivity with respect to performance, cost, time, and risk. Two conceptual tools are proposed. The first is a conceptual framework for value creation in PD, referred to here as the Value Creation Model. The second tool is the Value-Activity Map, which shows the relationships between specific activities and value attributes. These maps will allow a better understanding of the development of value in PD, will facilitate comparison of value development between separate projects, and will provide the information necessary to adapt process analysis tools (such as DSM) to consider value. The key questions that this research entails are: · What are the primary attributes of lifecycle value within PD? · How can one model the creation of value in a specific PD process? · Can a useful methodology be developed to quantify value in PD processes? · What are the tools necessary for application? · What PD metrics will be integrated with the necessary tools? The research milestones are: · Collection of value attributes and activities (September, 200) · Development of methodology of value-activity association (October, 2000) · Testing and refinement of the methodology (January, 2001) · Tool Development (March, 2001) · Present findings at July INCOSE conference (April, 2001) · Deliver thesis that captures a formalized methodology for defining value in PD (including LEM data sheets) (June, 2001) The research design aims for the development of two primary deliverables: a methodology to guide the incorporation of value, and a product development tool that will allow direct application.

Natural resource windfalls and efficiency of local government expenditures: evidence from Peru

We study the role of natural resource windfalls in explaining the efficiency of public expenditures. Using a rich dataset of expenditures and public good provision for 1,836 municipalities in Peru for period 2001-2010, we estimate a non-monotonic relationship between the efficiency of public good provision and the level of natural resource transfers. Local governments that were extremely favored by the boom of mineral prices were more efficient in using fiscal windfalls whereas those benefited with modest transfers were more inefficient. These results can be explained by the increase in political competition associated with the boom. However, the fact that increases in efficiency were related to reductions in public good provision casts doubts about the beneficial effects of political competition in promoting efficiency.

The impact of market and supply configurations on the costs of tendering in the construction industry

The cost of tendering in the construction industry is widely suspected to be excessive, but there is little robust empirical evidence to demonstrate this. It also seems that innovative working practices may reduce the costs of undertaking construction projects and the consequent improvement in relationships should increase overall value for money. The aim of this proposed research project is to develop mechanisms for measuring the true costs of tendering based upon extensive in-house data collection undertaken in a range of different construction firms. The output from this research will enable all participants in the construction process to make better decisions about how to select members of the team and identify the price and scope of their obligations.

An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams

This research has responded to the need for diagnostic reference tools explicitly linking the influence of environmental uncertainty and performance within the supply chain. Uncertainty is a key factor influencing performance and an important measure of the operating environment. We develop and demonstrate a novel reference methodology based on data envelopment analysis (DEA) for examining the performance of value streams within the supply chain with specific reference to the level of environmental uncertainty they face. In this paper, using real industrial data, 20 product supply value streams within the European automotive industry sector are evaluated. Two are found to be efficient. The peer reference groups for the underperforming value streams are identified and numerical improvement targets are derived. The paper demonstrates how DEA can be used to guide supply chain improvement efforts through role-model identification and target setting, in a way that recognises the multiple dimensions/outcomes of the supply chain process and the influence of its environmental conditions. We have facilitated the contextualisation of environmental uncertainty and its incorporation into a specific diagnostic reference tool.

Salesperson’s Personality, Motivation and Selling Performance : The Study of New Product Selling

In the highly competitive environment businesses invest big amounts of money into the new product development. New product success potentially depends on different factors among which salespeople play an important role. The aim of this paper is to explore the potential link between salespeople’s personality, motivation to sell new products and performance in selling new products. Based on the theoretical background of the Big Five personality dimensions, motivation and selling performance hypotheses were formulated and tested using statistical methods of correlation and regression analysis. The data was collected within one technologically intensive organization – ABB AB in Sweden using online web questionnaire and self-assessment measurements. Total investigation was conducted among organization’s salesforce. The findings confirm the importance of salesperson’s personality empirically showing that the latter significantly predicts both motivation and performance in selling new products. From all the Big Five Extraversion was confirmed to be the most important predictor of both motivation and performance in selling new products. Extraversion was found positively related with both motivation and performance in selling new products. Salespeople scoring high in Extraversion and especially possessing such characteristics as confident, energetic and sociable tend to be more motivated to sell new products and show higher performance results. Other personality dimensions such as Agreeableness, Conscientiousness, Neuroticism, and Openness to experience complexly approached are not proved to be significantly related neither with motivation nor performance in selling new products. The results are explained by the extreme importance of Extraversion in new product selling situation which analyzing in combination with the other personality dimensions suppresses the others. Finding regarding controlling for certain demographical characteristics of salespeople reveal that performance in selling new products is determined by selling experience. Salespeople’s age is not proved to be significantly related neither with motivation nor performance in selling new products. Findings regarding salespeople’s gender though proposing that males are more motivated to sell new products cannot be generalized due to the study limitations.

Information learning and the stability of fiat money

We analyze the stability of monetary regimes in a decentralized economy where fiat money is endogenously created, information about its value is imperfect, and agents only learn from their personal trading experiences. We show that in poorly informed economies, monetary stability depends heavily on the government's commitment to the long run value of money, whereas in economies where agents gather information more easily, monetary stability can be an endogenous outcome. We generate a dynamics on the acceptability of fiat money that resembles historical accounts of the rise and eventual colIapse of overissued paper money. Moreover, our results provide an explanation of the fact that, despite its obvious advantages, the widespread use of fiat money is a very recent development.

Evaluation of whole toasted and extruded soybean on the performance of broilers

This experiment was conducted to compare the performance of 1260 chicks fed diets containing soybean meal plus soybean oil (SBM + oil), whole extruded soybean (ESB) and whole steam toasted soybean (TSB), with two protein levels. A complete randomized design was used, with six treatments and 3 replicates of each sex. The treatments consisted of a factorial arrangement 2 x 3 x 2 to test three soybean types (SBM + oil, ESB and TSB), two protein levels (optimum and suboptimum) and two sexes. From 1 to 49 days of age, the tested soybean types did not affect the diet intake. However, ESB provided higher weight gain in relation to SBM + oil, but it did not differ from TSB. The feed:gain ratio obtained with ESB and TSB was better in relation to SBM + oil. There was no difference between the nutritional value of TSB and ESB, because they provided similar performance to the birds.

Performance evaluation of low environmental impact asphalt concretes using the mechanistic empirical design method based on laboratory fatigue and permanent deformation models

The "sustainability" concept relates to the prolonging of human economic systems with as little detrimental impact on ecological systems as possible. Construction that exhibits good environmental stewardship and practices that conserve resources in a manner that allow growth and development to be sustained for the long-term without degrading the environment are indispensable in a developed society. Past, current and future advancements in asphalt as an environmentally sustainable paving material are especially important because the quantities of asphalt used annually in Europe as well as in the U.S. are large. The asphalt industry is still developing technological improvements that will reduce the environmental impact without affecting the final mechanical performance. Warm mix asphalt (WMA) is a type of asphalt mix requiring lower production temperatures compared to hot mix asphalt (HMA), while aiming to maintain the desired post construction properties of traditional HMA. Lowering the production temperature reduce the fuel usage and the production of emissions therefore and that improve conditions for workers and supports the sustainable development. Even the crumb-rubber modifier (CRM), with shredded automobile tires and used in the United States since the mid 1980s, has proven to be an environmentally friendly alternative to conventional asphalt pavement. Furthermore, the use of waste tires is not only relevant in an environmental aspect but also for the engineering properties of asphalt [Pennisi E., 1992]. This research project is aimed to demonstrate the dual value of these Asphalt Mixes in regards to the environmental and mechanical performance and to suggest a low environmental impact design procedure. In fact, the use of eco-friendly materials is the first phase towards an eco-compatible design but it cannot be the only step. The eco-compatible approach should be extended also to the design method and material characterization because only with these phases is it possible to exploit the maximum potential properties of the used materials. Appropriate asphalt concrete characterization is essential and vital for realistic performance prediction of asphalt concrete pavements. Volumetric (Mix design) and mechanical (Permanent deformation and Fatigue performance) properties are important factors to consider. Moreover, an advanced and efficient design method is necessary in order to correctly use the material. A design method such as a Mechanistic-Empirical approach, consisting of a structural model capable of predicting the state of stresses and strains within the pavement structure under the different traffic and environmental conditions, was the application of choice. In particular this study focus on the CalME and its Incremental-Recursive (I-R) procedure, based on damage models for fatigue and permanent shear strain related to the surface cracking and to the rutting respectively. It works in increments of time and, using the output from one increment, recursively, as input to the next increment, predicts the pavement conditions in terms of layer moduli, fatigue cracking, rutting and roughness. This software procedure was adopted in order to verify the mechanical properties of the study mixes and the reciprocal relationship between surface layer and pavement structure in terms of fatigue and permanent deformation with defined traffic and environmental conditions. The asphalt mixes studied were used in a pavement structure as surface layer of 60 mm thickness. The performance of the pavement was compared to the performance of the same pavement structure where different kinds of asphalt concrete were used as surface layer. In comparison to a conventional asphalt concrete, three eco-friendly materials, two warm mix asphalt and a rubberized asphalt concrete, were analyzed. The First Two Chapters summarize the necessary steps aimed to satisfy the sustainable pavement design procedure. In Chapter I the problem of asphalt pavement eco-compatible design was introduced. The low environmental impact materials such as the Warm Mix Asphalt and the Rubberized Asphalt Concrete were described in detail. In addition the value of a rational asphalt pavement design method was discussed. Chapter II underlines the importance of a deep laboratory characterization based on appropriate materials selection and performance evaluation. In Chapter III, CalME is introduced trough a specific explanation of the different equipped design approaches and specifically explaining the I-R procedure. In Chapter IV, the experimental program is presented with a explanation of test laboratory devices adopted. The Fatigue and Rutting performances of the study mixes are shown respectively in Chapter V and VI. Through these laboratory test data the CalME I-R models parameters for Master Curve, fatigue damage and permanent shear strain were evaluated. Lastly, in Chapter VII, the results of the asphalt pavement structures simulations with different surface layers were reported. For each pavement structure, the total surface cracking, the total rutting, the fatigue damage and the rutting depth in each bound layer were analyzed.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

Identity, incentives and the value of information

We examine the impact of identity preferences on the interrelation between incentives and performance measurement. In our model, a manager identifies with an organization and loses utility to the extent that his actions conflict with effort-standards issued by the principal. Contrary to prior arguments in the literature, we find conditions under which a manager who identifies strongly with the organization receives stronger incentives and faces more performance evaluation reports than a manager who does not identify with the organization. Our theory predicts that managers who experience events that boost their identification with the firm can decrease their effort in short-term value creation. We also find that firms are more likely to employ less precise but more congruent performance measures, such as stock prices, when contracting with managers who identify little with the organization. In contrast, they use more precise but less congruent measures, such as accounting earnings, when contracting with managers who identify strongly with the firm.

Decision-usefulness of ideal cost- and ideal value accounting for valuation and stewardship

This paper contrasts the decision-usefulness of prototype accounting regimes based on perfect accounting for value, i.e. ideal value accounting (IVA), and perfect matching of cost, i.e. ideal cost accounting (ICA). The regimes are analyzed in the context of a firm with overlapping capacity investments where projects earn excess returns and residual income is utilized as performance indicator. Provided that IVA and ICA systematically differ based on the criterion of unconditional conservatism, we assess their respective decision-usefulness for different valuation- and stewardship-scenarios. Assuming that addressees solely observe current accounting data of the firm, ICA provides information which is useful for valuation and stewardship without reservation whereas IVA entails problems under specific assumptions.