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The purpose of this paper is to bridge the gap between physical and metaphysical entities in the context of product/system design. The paper talks about the grey area of human psychology and presents a theoretical framework for the identification and selection of psychological attributes for designers.

On the basis of a literature review, this paper identifies various psychological attributes affecting the performance of designers in a team environment and then analyses the same.

The paper talks about a new shift in engineering design and designs for maintainability of mechanical systems.

A procedure based on the analytic hierarchy process method is applied. The developed procedure is useful in the assessment and selection of coveted psychological attributes for personnel in general and for designers in particular.

The paper highlights the immense role of psychology in engineering design, especially in the design for maintainability of mechanical systems. The paper will be useful to researchers, designers, maintenance personnel and professionals from the domain of engineering design, irrespective of their field of application. This paper is equally useful for human resource and management professionals/researchers.

This paper aims to examine the perceptions of good design attributes and propose a model to estimate their relative importance through fundamental drivers. Design activities must understand and meet customer and producer expectations and deliver products in a profitable manner. Requirements analysis is conducted to understand customer expectations, but in new product development, this information can be available too late in the development cycle. Moreover, customer needs are often unclear to designers at early stages of design, with customers often unable to articulate their requirements or unaware of how a new product may solve problems or create complications. Evaluating non-product-specific drivers to generalized good product design attributes can help designers estimate important factors in early requirements analysis.

Quantification of the weight designers place in their mental models of what makes up a good product is determined from linear regression modeling, providing a more concrete evaluation of inherently subjective perceptions. A survey is deployed using Mechanical Turk^TM to collect perceptions of good product attributes and drivers through product case studies. Data are analyzed using a utility theory framework and importance of attributes is estimated from the importance of drivers.

A generalized model that estimates good design attributes from drivers is presented. This study also demonstrates that non-product-specific attribute importance can be extracted from specific product cases. An application example demonstrating the relative importance of good design attributes is given for different types of watches.

The approach is intended to supplement ordinary product design and development processes, and is not intended to replace market research and concept testing activities. Model coefficient weights are dependent on the quality of the data that was collected, which has limitations. While the current study included confounding variables, introducing interactions into the model could make attribute importance prediction more accurate.

While design requirements analysis is now central to modern design practice, these estimates can be available too late in the development cycle, especially when customers have no experience with the product type. The developed model quantifies design attributes that consumers, manufacturers and society as a whole use to distinguish if a product will be considered well designed. Product designers can better focus their development resources toward good design attributes based on guidance generated from generalized drivers.

Historically, requirements analysis is undertaken specific to the product being designed. This paper provides a model to give designers early guidance in a non-product-specific framework. The framework also considers good design attributes as holistic, including societal and producer concerns. Although all of the proposed good design attributes can be associated with a well-engineered product, it is unnecessary to design a product that performs exceptionally on every attribute. This model provides identification of the handful of attributes that can make the most significant difference for design success.

The purpose of this research is to test how varying the numbers of attributes and alternatives affects the use of heuristics and selective information processing in discrete choice experiments (DCEs). The effects of visual attribute and alternative non-attendance (NA) on respondent choices are analyzed.

Two laboratory experiments that combined eye tracking and DCEs were conducted with 109 and 117 participants in the USA. The DCEs varied in task complexity by the number of product attributes and alternatives.

Results suggest that participants ignore both single attributes and entire alternatives. Increasing the number of alternatives significantly increased attribute NA. Including NA in choice modeling influenced results more in more complex DCEs.

The current experiments did not test for choice overload. Future studies could investigate more complex designs. The choice environment affects decision-making. Future research could compare laboratory and field experiments.

Private and public sectors often use DCEs to determine consumer preference. Results suggest that DCEs with two alternatives are superior to DCEs with four alternatives because NA was lower in the two-alternative design.

This empirical research examined effects of attribute and alternative NA on choice modeling using eye tracking and DCEs with varying degrees of task complexity. Results suggest that accounting for NA reduces the risk of over- or understating the impact of attributes on choice, in that one avoids claiming significance for attributes that might not truly be preferred, and vice versa.

The purpose of this paper is to investigate a holistic way of incorporating biophilic building design that creates a restorative environment attractive to prospective urban hotel employees. This study additionally examines the role of perceived well-being from nature attributes and associated impacts on emotions and likelihood to choose to work for a hotel with nature attributes.

This study used a conjoint analysis to detect the most resotrative individual and combinations of biophilic attributes that can improve employee well-being. In addition, nature attributes influence on emotions and intentions to work for a hotel were analyzed.

Results showed that not all nature attributes are equally evaluated by urban hotel prospective employees. In this study, the authors found that natural lighting, outdoor green views and indoor landscaping are important factors in the evaluation of an urban hotel with biophilic features. However, this tendency varies when the sample was divided by prospective employees’ who perceived higher or lower levels of well-being would be influenced by nature attributes.

Unlike previous studies, the authors tested a multiattribute design and results demonstrate the perceived restorative effect of nature attributes in an environment on prospective employees. In addition to extending the biophilic design in hospitality literature, the authors provide practical suggestions to urban hotels incorporating biophilic design and propose that specific elements have the propensity to enhance the well-being of prospective employees and reinforce positive emotions and intentions to work for urban hotels that incorporate them.

The purpose of this paper is to construct the best combination of fabric printing pattern’s attributes to obtain the optimum design to meet the markets need.

This study reviewed the morphological analysis of fashion design expert groups regarding the fashionable fabric printing patterns, as well as the attribute preferences for different groups of fabric printing patterns through focus group discussions. In addition, the conjoint analysis was used to calculate the part-worth of these patterns’ design attributes and design levels to obtain the optimum design for fabric printing patterns.

The results of this study showed that the most importance of fabric attributes is the secondary pattern (32.59 percent), while the weights of shading element (24.80 percent) and primary pattern (24.46 percent) are almost the same. This study found that a wide range of intertwining image primary pattern can be applied to create interesting and popular fabric printing pattern designs. In practical applications of this result, when the primary pattern is supported by the buyer, fabric designers may use New Classic composite plants, with simple shading and different cycling configuration, to reproduce the optimum designs of the fabric printing patterns.

This proposed a novel solution to figure out the combination basis for optimizing fabric printing pattern designs. In addition, this result helps fabric printing pattern designers to establish an optimal design method for a specific brand to create a unique printing pattern design.

A method is proposed for handling multi-attribute judgment problems with a large number of attributes such as mobile phone features. To minimize the complication of multi-attributes and reduce the consumers’ choice task burden, this paper aims to suggest an integrated hierarchical survey design (IHSD) with the Kano model. The author compared the utility of mobile phone’s attributes for each market and for customer segment by analyzing empirical data on wear obtained from six Middle East and African countries, five Asia-Pacific countries and three European countries. Based on an IHSD of 10,200 respondents, brand, camera, memory and LTE (4G) play vital roles in all regions. In contrast, Wi-Fi, file-editor, MMS, LCD size and phone type are displayed as the least important attributes. The results of this study were successfully implemented for product planning, product development and marketing strategy in terms of price setting, features prioritizing and optimal designing for new products in the mobile phone company.

The first step was to list all possible features with the product planning team, product development team and market research specialists. The second step divided the selected features for designing a mobile phone into subgroups based on their functional characteristics by using the Kano model. The method for classifying features was determined using Kano questionnaire. The third step incorporated a fractional factorial design for the “must-be” choice-based conjoint (CBC) (Oppewal et al., 1994) which includes two factors: whether customers required the “one-dimensional” feature or the “attractive” feature, along with the “must-be” attributes. The consumers who selected the “must-be” features could choose both the “one-dimensional” feature and the “attractive” feature groups or one of the two feature groups in no particular order. Fractional factorial design was applied to both the “one-dimensional” features and the “attractive” features for individual CBCs. Random sequences of the combinations of attribute levels were generated for each of the three types of CBC analyses (“must-be”, “one-dimensional” and “attractive”). At the same time, the fourth step conducted a survey of the individual groups for the conjoint analysis on the functional characteristics of a mobile phone. The analysis of the accumulated data obtained from all the feature groups was completed using conditional logit models as part of the fifth step. In addition, the “must-be” CBC design was linked with the “one-dimensional” and “attractive” CBC designs. The sixth step was to analyze the accumulated results obtained from all the feature groups and estimate the usefulness of each feature’s level in the context of the CBC. Based on the results of the sixth step, the importance and willingness-to-pay of each attribute were estimated in the seventh step.

Use of the conjoint important score is aimed to expand the market by finding the different consumers’ needs across the regions. In detail, attributes such as “FM Transmitter”, “Touch screen” and “Health (heart rate)” are considered consumers’ new crucial needs in Europe, which would enable the product to superiorly differentiate itself from others to dominate the current market. On the other hand, it is shown that attributes such as “brand”, “mobile TV”, “external memory”, “mobile tracker” and “4G” are more important in Asia-Pacific. Therefore, if mobile manufacturers develop this sector more, it will grant mobile manufacturers the opportunity to lead the market. The only difference of the Middle East and African consumers is that “NFC” has a higher importance while the rest of the needs are very similar to those of Asia-Pacific. Regarding willingness-to-pay (WTP) among countries, the highest scoring utility, besides brand, appeared to be associated with the camera function in all countries. Especially, relatively low utility value was given in Wi-Fi and File-editer, MMS, LCD size and Phone type. In a value-based approach, the price of a product is based on the perceived valuation by the target customers. The research in the field of pricing is of ample importance. This is because price is the only element of the marketing mix that generates income. All other elements, such as advertising and promotion, product development, selling effort, distribution and packaging, involve expenditures (Monroe, 2003). Regarding among regions, the needs for 3G and the internet-related feature (WAP, Wi-Fi, etc.) in the emerging market are low compared to those for 4G and internet-related feature in the mature market. Also, the needs for productivity and advanced features, such as camera and e-mail, are lower in Asia-Pacific than in Europe. It is therefore recommended that manufactures and marketers of mobile phones should consider producing and selling phones with modern technology features that are more durable and of highly quality.

The integrated hierarchical survey by function with the Kano model proves to be a highly useful, efficient and accurate methodology for understanding a consumer mobile phone behavior. Although the proposed method was applied to designs of mobile phones in the emerging and mature markets, its accuracy was not compared with the traditionally used methods such as CBC, adaptive conjoint analysis and hybrid method. This is left for further areas of research.

The results of this research study correspond with previous studies conducted (Pakola et al., 2010; Das, 2012; Malaasi, 2012, 2008; Dziwornu, 2013), which consider the features of mobile phone as a crucial factor in consumer buying decision in all countries. It is significant that this study made huge impact on mobile phone manufacturers in several ways. It has been converted into product development with consumer-oriented approach. The pricing policy has been changed from cost-based pricing into value-based pricing; and marketing strategy has been changed from an unsystematic function into a systematic and consistent one.

The proposed method with the Kano model proved to be a practical and efficient tool for decision-making, as it helped mobile manufacturers to better understand how customers evaluate and perceive quality attributes. The Kano model was used to explain how the quality attributes can be classified into mainly three categories of perceived quality: “must-be”, “one-dimensional” and “attractive”. It has lots of benefits in terms of cost and time reduction and is expected to bring a great effect into the industrial field.

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

The poor quality of design documentation has been identified as a significant contributor to delays, rework and cost overruns on construction projects in South Africa. Despite this, limited research has been undertaken to specifically investigate the quality of design documentation. This in turn hampers efforts aimed at improving the quality of the design documents. The aim of this study is to identify the key quality attributes of design documentation and determine the extent to which the design documents issued on South African construction projects are perceived to incorporate the quality attributes.

A survey questionnaire was distributed among civil engineering design consultants and contractors in the South African construction industry. Responses to a total of 120 completed questionnaires were statistically analysed. The relative importance and extent of incorporation of the quality attributes was determined based on the mean scores.

It emerged from the study that the two key quality attributes of design documentation were legibility and coordinated design documentation. Attributes with the least importance were relevancy and certainty. Regarding the incorporation of the quality attributes, the design documents were rated highly with respect to their legibility and clarity. The quality of the documentation was deemed inadequate in terms of accuracy and certainty.

The findings provide valuable insight to stakeholders involved in developing initiatives aimed at improving the quality of design documentation and as a result construction project performance.

The study provides empirical evidence and extends the literature on design documentation quality especially from the perspective of South Africa, a developing country.

In the process of designing new clothes, designers should identify specific user groups’ preferences and attitudes toward certain types of design, ascertain the design elements that make clothes popular in the market, and combine these elements to devise the best clothing design scheme. The purpose of this paper is to discover which design elements influence dress purchases and how age affects consumers’ choices in regard to these elements.

This study uses conjoint analysis in dress design to provide an effective method for designers to identify consumers’ preferences. First, the important attributes and attribute levels of dress design were determined. Next, the experimental samples for the attitude measurement chart were generated by orthogonal design. Finally, the data of 318 samples were analyzed by conjoint analysis to determine consumers’ preferences.

The results revealed that the “silhouette” attribute is the most important decision criterion for dress purchase, followed by the “dress length” attribute. In contrast, the “waistline height” attribute is perceived as least important. The study also identified the dress design features’ preferences of consumers of different ages. According to the results of the analysis, user groups’ preferences and acceptability regarding different design features were revealed, and the favorite dress design portfolio for age-specific consumers was obtained.

Currently, there is little information in the literature about consumers’ preferences regarding dress design. In this study, the use of conjoint analysis reveals and visualizes complex statistical results. This research approach is also applicable to the design and decision-making processes used for other apparel, and it can help designers better incorporate different users’ needs into clothing design.

The purpose of this paper is to use the concepts of the multi-attribute utility theory to develop a model to evaluate the design of low-density residential units to increase the profit of the company from a certain design, by assessing the changes in the market shares as a result of the built unit’s attributes.

The proposed platform consists of two stages: Stage I or relational model development and Stage II or design evaluation. Stage I is concerned with developing a mathematical model that links design variables (e.g. the R-Value of the building envelope and construction material) with the assessment attributes (e.g. price and carbon emissions). Stage II ensures the fulfillment of the corporation’s goals in maximizing profit and market shares using multi-attribute utility theory.

The application of the proposed model on a case study – a single-family house – shows that reducing the selling price of the unit is not always the best marketing strategy builders should pursue to increase their sales and accordingly their profit, as accounting for other attributes (e.g. performance, operational cost and environmental impact) leads to larger changes in the market shares and accordingly in profit.

The limitations of this research are manifested in the following points: it does not account for the impact of the marketing campaigns on the market shares; it considers the profit as a percentage of the construction cost; and it has not been validated on high-density residential buildings.

This research provides speculative builders with a platform that allows the objective evaluation of houses’ designs prior to introducing them to the market so builders can increase their market shares and consequently their profit. The proposed platform also contributes to increasing the sustainable performance of the housing industry, as it allows for the assessment of the design against economic, environmental and social attributes concurrently, which ensures a balanced consideration of the built houses on sustainability pillars.

The proposed platform for design evaluation extends the assessment attributes beyond the traditionally considered economic and environmental attributes. By doing so, it assists decision-makers in evaluating the potential social influence of the proposed design and, as a result, reduces the unwanted impact.

This research combines the concepts of multi-attribute utility with market studies to develop an objective decision support tool for evaluating the design of speculative houses to increase the sustainable performance of the builders without compromising on their profit.