Abstract: Job preferences are a well-developed research field. Many studies analyze the preferences using simple ratings with a sample of university graduates. The current study analyzes the preferences with a mixed method approach of a qualitative preliminary study and adaptive conjoint-analysis. Preconditions of accepting job offers are clarified for professionals in the industrial sector. It could be shown that, e.g. wages above the average are critical and that career opportunities must be seen broader than merely a focus on formal personnel development programs. The results suggest that, to be effective with their recruitment efforts, employers must take into account key desirable job attributes of their target group.
Abstract: Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.
Abstract: A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.
Abstract: In today’s business environment, companies should
make strategic decisions to gain sustainable competitive advantage.
Order selection is a crucial issue among these decisions especially for
steel production industry. When the companies allocate a high
proportion of their design and production capacities to their ongoing
projects, determining which customer order should be chosen among
the potential orders without exceeding the remaining capacity is the
major critical problem. In this study, it is aimed to identify and
prioritize the evaluation factors for the customer order selection
problem. Conjoint Analysis is used to examine the importance level
of each factor which is determined as the potential profit rate per unit
of time, the compatibility of potential order with available capacity,
the level of potential future order with higher profit, customer credit
of future business opportunity, and the negotiability level of
production schedule for the order.
Abstract: Since the advent of the information era, the Internet has
brought various positive effects in everyday life. Nevertheless,
recently, problems and side-effects have been noted. Internet
witch-trials and spread of pornography are only a few of these
problems.In this study, problems and causes of malicious replies on
internet boards were analyzed, using the key ideas of game theory. The
study provides a mathematical model for the internet reply game to
devise three possible plans that could efficiently counteract malicious
replies. Furthermore, seven specific measures that comply with one of
the three plans were proposed and evaluated according to the
importance and utility of each measure using the orthogonal array
survey and SPSS conjoint analysis.The conclusion was that the most
effective measure would be forbidding unsigned user access to
malicious replies. Also notable was that some analytically proposed
measures, when implemented, could backfire and encourage malicious
replies.
Abstract: This paper deals with the application of a fuzzy set in
measuring teachers- beliefs about mathematics. The vagueness of
beliefs was transformed into standard mathematical values using a
fuzzy preferences model. The study employed a fuzzy approach
questionnaire which consists of six attributes for measuring
mathematics teachers- beliefs about mathematics. The fuzzy conjoint
analysis approach based on fuzzy set theory was used to analyze the
data from twenty three mathematics teachers from four secondary
schools in Terengganu, Malaysia. Teachers- beliefs were recorded in
form of degrees of similarity and its levels of agreement. The
attribute 'Drills and practice is one of the best ways of learning
mathematics' scored the highest degree of similarity at 0. 79860 with
level of 'strongly agree'. The results showed that the teachers- beliefs
about mathematics were varied. This is shown by different levels of
agreement and degrees of similarity of the measured attributes.
Abstract: This research elaborates decision models for product
innovation in the early phases, focusing on one of the most widely
implemented method in marketing research: conjoint analysis and the
related conjoint-based models with special focus on heuristics
programming techniques for the development of optimal product
innovation. The concept, potential, requirements and limitations of
conjoint analysis and its conjoint-based heuristics successors are
analysed and the development of conceptual framework of Genetic
Algorithm (GA) as one of the most widely implemented heuristic
methods for developing product innovations are discussed.