Examination of Decision Factors in the Process of Buying Kitchen Furniture Using Conjoint Analysis

Liker, Branko; Stirn, Lidija Zadnik; Bučar, Dominika Gornik; Hrovatin, Jasna

doi:10.5552/drind.2016.1525

Cited by 2 publications

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“…In the contemporary global market, furniture manufacturers are facing strong competition (Zadnik Stirn et al 2016). In order to maintain their market share, they have to improve their manufacturing and management processes and introduce innovations both in products and processes, as well as to be familiar with the consumer's needs (Fabisiak 2017, Oblak et al 2017.…”

Section: Introduction 1 Uvodmentioning

confidence: 99%

Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling

et al. 2018

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In the paper, by way of background, the role of Polish furniture industry in the world and in Europe is discussed and current trends in the fi eld of furniture manufacturing management are presented. Further, an analysis of the technological process in a furniture company is performed and the research questions are identifi ed. Based on this, the main aim of the research is provided-a concept of a new lean production control system based on Glenday sieve, artifi cial neural networks and simulation modeling. The aim of the present approach is to plan and execute the production program effectively and maximize the use of workstations at variable and hardly predictable demand for sets of furniture. The paper presents the methodological approach, results and discussion on the suggested solution.

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Section: Introduction 1 Uvodmentioning

confidence: 99%

Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling

et al. 2018

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Koa (Acacia koa A. Gray), a species endemic to the Hawaiian Islands, has ecological, cultural, and economic significance. Its wood is prized globally but today, most woodworkers only use koa wood from dead and dying old-growth trees. The general perception of wood from young-growth koa is that it lacks the color and figure of old-growth wood and is thus less appealing to consumers. To evaluate consumer preference of koa attributes, a conjoint choice experiment was conducted using randomly combined levels of attributes, including color, figure (curl), and price, with six identically shaped bowls from which respondents selected their preferences. The survey was conducted at six locations on O'ahu (372 respondents) to poll a variety of koa product consumers. Latent class analysis software was used to separate respondents into distinct classes based on expressed preferences. The results identified five classes of respondents. Class 1 (24% of respondents) showed significant preference for lower prices, medium color, and non-curly bowls. Class 2 (22% of respondents) showed significant preference for light colored and curly bowls. Class 3 (20% of respondents) showed significant preference for light or medium colored and curly bowls. Class 4 (19% of respondents) significantly preferred lower prices and light or medium colored bowls. Class 5 (15% of respondents) also significantly preferred lower prices but they significantly preferred darker colored and curly bowls as well. Opportunities exist for koa woodworkers to create products manufactured from young-growth koa wood that appeal to different market segments. The ability to substitute young-growth koa for the decreasing supply of old-growth wood can aid in promoting active management of the species.

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Examination of Decision Factors in the Process of Buying Kitchen Furniture Using Conjoint Analysis

Abstract: • The aim of this research was to determine the relative importance of three factors relevant for buying wooden kitchen furniture in Croatia and

Cited by 2 publications

References 11 publications

Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling

Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling

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