Tufan Koc

Organizational determinants of innovation capacity in software companies

This study investigates the relationship between organizational factors and innovation capacity in software development companies. By means of this investigation this paper aims to determine the organizational factors that have significant impact on the innovation capacity of companies. For this purpose an empirical research including 91 small and medium sized software development companies was conducted. A factor analysis and regression based methodology were used to analyze the collected data. The study reveals that the innovative software companies regard three basic predictors significantly important for innovation capacity. Idea generation and human resource impacted the innovation capacity positively. However, the third predictor, cross-functional integration impacted the innovation capacity negatively.

The selection of technology forecasting method using a multi-criteria interval-valued intuitionistic fuzzy group decision making approach

Technological forecasting is a tool for organizations to develop their technology strategies. The quality of forecasting is extremely important for the accuracy of the results and in turn company future. Therefore a proper selection methodology of forecasting technique that considers the characteristics of technology and resources needed such as cost, time is essential. On the other hand, although many forecasting techniques are available, there is a high uncertainty in choosing the most appropriate technique among a set of available techniques. In this paper interval valued intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is proposed for the solution of technological forecasting technique selection problem. The proposed method includes seven selection criteria and twelve forecasting technique alternatives. The methodology is applied for 3D TV technology. The results revealed that Fisher Pry method is found as the most appropriate method for forecasting since it has the highest closeness coefficient.

Measuring the degree of novelty of innovation based on Porter's value chain approach

Measurement of the degree of novelty is extremely important to avoid risk and carry out a sound innovation process. This research attempts to offer a different conceptual framework to understand and measure the degree of novelty of an innovation. It is based on Porters value chain approach and proposes a process-oriented model that considers the possible impact of a particular technology on the discrete business processes in a firms value chain. A new technology employed by companies is expected to impact the value chain activities by requiring reorganization in the current value chain of the company. The 2-additive Choquet integral is used to measure how such impacts will be reflected on the degree of novelty of that technology. An application of the proposed model to technology alternatives for the energy sources of electrical automobiles is presented. The model is applied in a battery manufacturing company. Technology alternatives to be measured in terms of the degree of novelty consist of the nickel metal hydride battery, the lithium-ion battery and fuel cell technologies. The results indicate that fuel cell technology has the highest degree of novelty among the three energy sources for electrical automobiles.

Development of a justification tool for advanced technologies: An example for RFID

Growing competition and increasing demands from customers are forcing small manufacturers to consider investments in advanced technologies. For many reasons, such investments are often difficult to justify by means of a traditional economic analysis alone. As a result, it is often necessary to consider the system wide benefits associated with ATs in order to justify their adoption. The objective of this paper is to develop an AT project selection model that takes particularly the uncertainty, that most of the advanced technology project has, into consideration. An example for AT projects that also includes RFID is used to illustrate the proposed approach.

Manufacturing Flexibility as a Strategy to Deal with Uncertainty

In uncertain environments, increased flexibility is necessary to facilitate the development of fast adaptation capability that lead to an effective environmental response. Manufacturing companies generally have some problems about coping with the uncertainty in their industries and they tend to increase the flexibility level of their manufacturing system. Measurement of flexibility is required for this purpose. This paper intends to develop an entropy based model to measure flexibility. The model proposed includes manufacturing characteristics such as type of machinery, number and type of operations, routing for each product as well as time spend for operations, machine set up activities and material handling. An application of the model is performed in a job shop. Flexibility level is measured and the association between the total entropy value and flexibility level is discussed.

Technology forecasting: Focusing on main system or aggregation of subsystems

A complex product system consists of numerous subsystems organized in a hierarchical fashion. In literature there exists a tendency in measuring the life cycle of main system by using parameters which characterize the performance of that main technology. This may lead to problems in investment decisions for technology renewal since the forecast of main system technology lifecycle is associated but does not fully represent its subsystems lifecycle. This paper intends to clarify this problem with a case study by showing while the main system is in its midlife; some of the subsystems are approaching their limits and requires urgent radical investment. As a case study refrigerator system is used and the relevant life cycles are obtained using growth curves as a technology forecasting tool. The findings are discussed and suggestions for the need of a multiple level of analysis are given in the discussion section.