Intellectual Property Protection : an External Factor that Influences a Foreign Company’s Market Entry Mode into a Prospective Market

Intellectual Property Protection is been understood in this paper as IP laws and enforcement of these laws in order to protect intellectual property rights. The goal of this research work is to understand how Swedish companies view issues regarding to Intellectual Property Protection (IPP) and how it influences a foreign company?s market entry mode. In order to achieve this objective, the Nigerian market situation and its? laws that govern IPP will be used to analyzed this issue. This paper argues that IPP is an important factor that influences a company?s entry mode and this argument finds IP laws and enforcement as two variables that influence the market while the market situation influences the foreign company. In carrying out this research literature was reviewed and interviews carried out. The research methodology section has presented a qualitative research and explains the nature of the interview stages that have been used to achieve the goals concerning the findings of the empirical data. A qualitative method was adopted by carrying out in-depth semi-structured interviews. The empirical data collected from the investigation were gathered and analyzed based on the research questions. The findings show that IPP of a host market influences a potential foreign company through the market situation that is also influenced by IP laws and enforcement. The outcome of these findings argues that the Swedish companies that were interviewed in this research will enter the Nigerian market through an intermediary mode. This has been based on the current IPP system of Nigerian.

Module property verification : A method to plan and perform quality verifications in modular architectures

Modular product architectures have generated numerous benefits for companies in terms of cost, lead-time and quality. The defined interfaces and the module’s properties decrease the effort to develop new product variants, and provide an opportunity to perform parallel tasks in design, manufacturing and assembly. The background of this thesis is that companies perform verifications (tests, inspections and controls) of products late, when most of the parts have been assembled. This extends the lead-time to delivery and ruins benefits from a modular product architecture; specifically when the verifications are extensive and the frequency of detected defects is high. Due to the number of product variants obtained from the modular product architecture, verifications must handle a wide range of equipment, instructions and goal values to ensure that high quality products can be delivered. As a result, the total benefits from a modular product architecture are difficult to achieve. This thesis describes a method for planning and performing verifications within a modular product architecture. The method supports companies by utilizing the defined modules for verifications already at module level, so called MPV (Module Property Verification). With MPV, defects are detected at an earlier point, compared to verification of a complete product, and the number of verifications is decreased. The MPV method is built up of three phases. In Phase A, candidate modules are evaluated on the basis of costs and lead-time of the verifications and the repair of defects. An MPV-index is obtained which quantifies the module and indicates if the module should be verified at product level or by MPV. In Phase B, the interface interaction between the modules is evaluated, as well as the distribution of properties among the modules. The purpose is to evaluate the extent to which supplementary verifications at product level is needed. Phase C supports a selection of the final verification strategy. The cost and lead-time for the supplementary verifications are considered together with the results from Phase A and B. The MPV method is based on a set of qualitative and quantitative measures and tools which provide an overview and support the achievement of cost and time efficient company specific verifications. A practical application in industry shows how the MPV method can be used, and the subsequent benefits

Strategic alliances in a town centre : Stakeholder’s perceptions of property owner’s role

In order for town centres to manage increased competition in retailing, co-operation between stakeholders in a strategic alliance has become more important. A typical set of stakeholders in a strategic alliance for strengthening retailingare retailers, local authorities and property owners. The roles of retailer’sand local authorities’ are well researched. However, the role of property owners is not. The aim of this paper seeks to unfold the role of property owners in a strategic alliance. This is a case study of a medium-sized town in which semi-structured interviews with different stakeholders were conducted. In the chosen town there is a TCM alliance co-operation at work. The above mentioned stakeholders are possible members in an alliance. The case studied shows a fragmented property owner market with no dominant property owner, as it is in many medium-sized towns. Our study shows that many stakeholders look at the role of property owners as crucial for town centre development. However, property owners do not see that they can significantly contribute to or benefit from the development.The main reasons for this opinion are that they consider themselves as not having enough resources or the capability to influence the town development.

Likelihood estimate of treatment effects under selection bias

We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.