An investigation of customer delight during product evaluation: Implications for the development of desirable products

This paper reports findings from three research methods used to study customer delight during product evaluation. The results are framed in terms of existing models, high-lighting inadequacies in the assumptions these models make. Implications for product development are proposed in the form of practical strategies for understanding and delighting customers. © IMechE 2007.

品牌表现评价反应时与关注特性的关系

The decision making of customers has been a great concern in the field of customer research. Although China has entered the era of brand consumption and development, due to the different understanding of the regarded attributes between companies and customers, the phenomenon of “The awarded products don’t sell well, but the products which sell well can’t get the award.” appears. At the same time there is little research on the relationship between the brand and the customers has been conducted in China now. Traditional research on customer psychology employ questionnaires, depth interview and group discussions as the major methods. In cognitive psychology, the limitation of explicit memory has been revealed by implicit memory; moreover, unconscious cognition and implicit memory can also influence customers' remark of the brand. Therefore, the traditional methods are not accurate enough. Reaction time is an effective way to reveal testing equality, and it can also reveal implicit cognition. Based on the researches intends to investigate the validity of attention attributes in the method of reaction time by questionnaires and time reaction testing of 360 customers in 3 cities, which may, probably, overcomes the limitation of the traditional research methods. The 352 valid samples were analyzed by SPSS. The results showed there was no distinct corresponding relationship between the product attributes and reaction time. The different key attributes from questionnaire importance rating and the shortest reaction time standards were used to regressively analyze the results of customers’ overall rating (such as overall satisfaction,objective quality, recommend intention).The results indicated that the coefficiency of regression of the special attributes chosen from reaction time to overall rating was distinct, while the coefficiency of the special attributes chosen from importance rating to overall rating was not. The main conclusions are: 1. Regarded attributes can be obtained by the reaction time of brand performance rating. 2. Regarded attributes obtained by the reaction time of brand performance rating are more accurate than those by importance rating questionnaires. 3. The brand’s core attributes should includes regarded attributes during the decision making process.

Construct and content validity of the Greek version of the birth satisfaction scale (G-BSS).

Background: ‘Birth Satisfaction’ is a term that encompasses a woman’s evaluation of her birth experience. The term includes factors such as her appraisal of the quality of care she received, a personal assessment of how she coped, and her reconstructions of what happened on that particular day. Her accounts may be accurate or skewed, yet correspond with her reality of how events unfolded. Objective: To evaluate properties of an instrument designed to measure birth satisfaction in a Greek population of postnatal women. Study design: We assessed factor structure, internal consistency, divergent validity and known-groups discriminant validity of the 30-item Greek Birth Satisfaction Scale – Long Form (30-item G-BSS-LF) and its revised version the 10-item Greek-BSS-Revised (10-item-G-BSS-R), using survey data collected in Athens. Participants: A convenience sample of healthy Greek postnatal women (n = 162) aged 22–46 years who had delivered between 34 and 42 weeks’ gestation. Results: The 30-item-G-BSS-LF performed poorly in terms of factor structure. The short-form 10-item-G-BSS-R performed well in terms of measurement replication of the English equivalent version as a multidimensional instrument. The short-form 10-item-G-BSS-R comprises three subscales which measure distinct but correlated domains of: (1) quality of care provision (4 items), (2) women’s personal attributes (2 items), and (3) stress experienced during labour (4 items). Key conclusions: The 10-item-G-BSS-R is a valid and reliable multidimensional psychometric instrument for measuring birth satisfaction in Greek postnatal women.

Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences

J. Keppens and Q. Shen. Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences. Journal of Artificial Intelligence Research, 21:499-550, 2004.

Qualidade nos serviços públicos

Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências da Comunicação, especialização em Relações Públicas.

Trade & Cap: A Customer-Managed, Market-Based System for Trading Bandwidth Allowances at a Shared Link

We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" – both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.

Identifying sources of global contention in constraint satisfaction search

Much work has been done on learning from failure in search to boost solving of combinatorial problems, such as clause-learning and clause-weighting in boolean satisfiability (SAT), nogood and explanation-based learning, and constraint weighting in constraint satisfaction problems (CSPs). Many of the top solvers in SAT use clause learning to good effect. A similar approach (nogood learning) has not had as large an impact in CSPs. Constraint weighting is a less fine-grained approach where the information learnt gives an approximation as to which variables may be the sources of greatest contention. In this work we present two methods for learning from search using restarts, in order to identify these critical variables prior to solving. Both methods are based on the conflict-directed heuristic (weighted-degree heuristic) introduced by Boussemart et al. and are aimed at producing a better-informed version of the heuristic by gathering information through restarting and probing of the search space prior to solving, while minimizing the overhead of these restarts. We further examine the impact of different sampling strategies and different measurements of contention, and assess different restarting strategies for the heuristic. Finally, two applications for constraint weighting are considered in detail: dynamic constraint satisfaction problems and unary resource scheduling problems.

Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.

Satisfaction and acceptance with learning management systems

More and more often, universities make the decision to implement integrated learning management systems. Nevertheless, these technological developments are not realized without any trouble, and are achieved with more or less success and user satisfaction (Valenduc, 2000). It is why the presented study aims at identifying the factors influencing learning management system satisfaction and acceptance among students. The Technology Acceptance model created by Wixom and Todd (2005) studies information system acceptance through user satisfaction, and has the benefit of incorporating several ergonomic factors. More precisely, the survey, based on this model, investigates behavioral attitudes towards the system, perceived ease of use, perceived usefulness, as well as system satisfaction, information satisfaction and also incorporates two groups of factors affecting separately the two types of satisfaction. The study was conducted on a representative sample of 593 students from a Brussels university which had recently implemented an integrated learning management system. The results show on one hand, the impact of system reliability, accessibility, flexibility, lay-out and functionalities offered on system satisfaction. And on the other hand, the impact of information accuracy, intelligibility, relevance, exhaustiveness and actualization on information satisfaction. In conclusion, the results indicate the applicability of the theoretical model with learning management systems, and also highlight the importance of each aforementioned factor for a successful implantation of such a system in universities.

Body image and body satisfaction differ by race in overweight postpartum mothers.

BACKGROUND: Body image (BI) and body satisfaction may be important in understanding weight loss behaviors, particularly during the postpartum period. We assessed these constructs among African American and white overweight postpartum women. METHODS: The sample included 162 women (73 African American and 89 white) in the intervention arm 6 months into the Active Mothers Postpartum (AMP) Study, a nutritional and physical activity weight loss intervention. BIs, self-reported using the Stunkard figure rating scale, were compared assessing mean values by race. Body satisfaction was measured using body discrepancy (BD), calculated as perceived current image minus ideal image (BD<0: desire to be heavier; BD>0: desire to be lighter). BD was assessed by race for: BD(Ideal) (current image minus the ideal image) and BD(Ideal Mother) (current image minus ideal mother image). RESULTS: Compared with white women, African American women were younger and were less likely to report being married, having any college education, or residing in households with annual incomes >$30,000 (all p < 0.01). They also had a higher mean body mass index (BMI) (p = 0.04), although perceived current BI did not differ by race (p = 0.21). African Americans had higher mean ideal (p = 0.07) and ideal mother (p = 0.001) BIs compared with whites. African Americans' mean BDs (adjusting for age, BMI, education, income, marital status, and interaction terms) were significantly lower than those of whites, indicating greater body satisfaction among African Americans (BD(Ideal): 1.7 vs. 2.3, p = 0.005; BD(Ideal Mother): 1.1 vs. 1.8, p = 0.0002). CONCLUSIONS: Racial differences exist in postpartum weight, ideal images, and body satisfaction. Healthcare providers should consider tailored messaging that accounts for these racially different perceptions and factors when designing weight loss programs for overweight mothers.

Implementation of customer relationship management and inventory control software: a multiple case study of small retailers

Gemstone Team Small Business Solutions