Untersuchung der Präferenzen russischer Fachbesucher für ausgewählte Messeleistungen

Der vorliegende Beitrag analysiert Präferenzen russischer Fachbesucher für ausgewählte Messeleistungen. Als Methode wurde die Choice-Based Conjoint Analyse eingesetzt, die eine realitätsnahe Erfassung von Auswahlentscheidungen und somit die Abbildung des Verhaltens der Probanden ermöglicht. Mit Hilfe des Latent Class Verfahrens wurden anschließend insgesamt zwei Segmente mit unterschiedlichen Präferenzen für Eintrittspreis, Internetseite, Fachprogramm, Präsentationen sowie Besucherservice ermittelt. -- E N G L I S H V E R S I O N: This paper presents an analysis of preferences of Russian trade visitors for selected exhibit attributes. We used Choice Based Conjoint Analysis to establish realistic measurement of choice tasks and hence to determine respondents behaviour. By conducting latent class analysis we extracted two segments of Russian trade visitors with different preferences for price, web presence, business program, presentations and visitor-service.Präferenzanalyse,Choice-Based Conjoint Analyse,Benefitsegmentierung,russische Messe,Preference Analysis,Choice Based Conjoint Analysis,Benefit segmentation,Russian exhibition

Adjunct Therapy in Type 1 Diabetes: A Survey to Uncover Unmet Needs and Patient Preferences Beyond HbA1c Measures.

Background: Adjunct therapy can help patients with type 1 diabetes achieve glycemic goals while potentially mitigating some of the side effects of insulin. In this study, we used a patient survey to identify the unmet needs in type 1 diabetes therapy, patient views of treatment benefit-risk trade-offs, and patient preferences for the use of an adjunct therapy. Methods: A quantitative survey was sent to 2084 adults with type 1 diabetes in November 2017. "Jobs-to-be-done" and conjoint analyses were performed on survey responses to identify unmet needs and the importance of treatment-associated benefits and risks to patients. A 5-point Likert scale measured the importance and satisfaction with patients' current therapy, and with gaps relating to unmet needs. In the conjoint analysis, patients were asked to choose between "packages" of attributes of two doses of adjunct therapy (200 and 400 mg) and placebo, based on established benefits and side effects. Results: A total of 1313 patients (63%) responded. The greatest unmet needs identified were simplifying treatment, lowering/maintaining glycated hemoglobin (HbA1c), reducing mental effort, and increasing time in range (TIR). Conjoint analysis showed that reductions in body weight and TIR had the highest attribute importance (25% and 18%, respectively). The majority (93%) of patients had a preference for the adjunct therapy (either dose) over placebo. Conclusions: This survey highlights the importance of measures beyond HbA1c, such as treatment simplification and TIR, and patient preference for adjunct therapies that help address unmet needs in type 1 diabetes treatment

Venture Capitalists' Evaluations of Start-up Teams: Trade-offs, Knock-out Criteria, and the Impact of VC Experience

The start-up team plays a key role in venture capitalists' evaluations of venture proposals. Our findings go beyond existing research, first by providing a detailed exploration of VCs' team evaluation criteria, and second by investigating the moderator variable of VC experience. Our results reveal utility trade-offs between team characteristics and thus provide answers to questions such as "What strength does it take to compensate for a weakness in characteristic A?" Moreover, our analysis reveals that novice VCs tend to focus on the qualifications of individual team members, while experienced VCs focus more on team cohesion. Data was obtained in a conjoint experiment with 51 professionals in VC firms and analyzed using discrete choice econometric models. (author's abstract

Latent class analysis for segmenting preferences of investment bonds

Market segmentation is a key component of conjoint analysis which addresses consumer preference heterogeneity. Members in a segment are assumed to be homogenous in their views and preferences when worthing an item but distinctly heterogenous to members of other segments. Latent class methodology is one of the several conjoint segmentation procedures that overcome the limitations of aggregate analysis and a-priori segmentation. The main benefit of Latent class models is that market segment membership and regression parameters of each derived segment are estimated simultaneously. The Latent class model presented in this paper uses mixtures of multivariate conditional normal distributions to analyze rating data, where the likelihood is maximized using the EM algorithm. The application focuses on customer preferences for investment bonds described by four attributes; currency, coupon rate, redemption term and price. A number of demographic variables are used to generate segments that are accessible and actionable.peer-reviewe

Managing customer knowledge during the concept development stage of the new food product development process

New product development (NPD) is a knowledge intensive process where the generation of new ideas and concepts requires detailed knowledge of both products and customers. The high reported failure rates for innovative functional beverages suggest an inability to manage customer knowledge effectively, as well as a lack of knowledge management between functional disciplines involved in the NPD process. This research explored the concept of managing customer knowledge at the early stages of the NPD process, through the use of advanced concept optimisation methods, and applied it to the development of a range of functional beverages. A conjoint - based survey was administered to four hundred customers in Ireland. This research identified two hypothetical functional beverage concepts with high levels of customer acceptance. Managing customer knowledge during the concept development stage of the NPD process can assist firms overcome customer acceptance issues associated with innovative products. Methodologies that advance both a firm's understanding of customers' choice motives and value systems, and its knowledge management process, can increase the chances of new product success in international food and beverage markets.Knowledge Management, New Product Development, Functional Beverages, Marketing,

The development of a measure of social care outcome for older people. Funded/commissioned by: Department of Health

An essential element of identifying Best Value and monitoring cost-effective care is to be able to identify the outcomes of care. In the field of health services, use of utility-based health related quality of life measures has become widespread, indeed even required. If, in the new era of partnerships, social care outcomes are to be valued and included we need to develop measures that reflect utility or welfare gain from social care interventions. This paper reports on a study, commissioned as part of the Department of Health’s Outcomes of Social Care for Adults Initiative, that developed an instrument and associated utility indexes that provide a tool for evaluating social care interventions in both a research and service setting. Discrete choice conjoint analysis used to derive utility weights provided us with new insights into the relative importance of the core domains of social care to older people. Whilst discrete choice conjoint analysis is being increasingly used in health economics, this is the first study that has attempted to use it to derive a measure of outcome

UNDERSTANDING THE BENEFIT STRUCTURE OF CLOUD STORAGE AS A MEANS OF PERSONAL ARCHIVING - A CHOICE-BASED CONJOINT ANALYSIS

While cloud storage has seen an increasing rise in demand and diffusion, it is also becoming a commodity, which makes it more difficult for cloud storage providers to be competitive in the market. To be successful as a storage provider, it is crucial to understand customer preferences so that these can be addressed accordingly. In this paper, we investigate consumer cloud storage choice decisions by employing a conjoint analysis that is based on empirical data collected from 340 participants and analyzed by means of hierarchical Bayes estimation. Our findings indicate significant differences in consumer preferences for price, storage capacity, encryption mechanism and accessibility. Based on these differences, we derive three consumer clusters that also exhibit differences in, e.g., their privacy concerns and risk beliefs. Based on our findings, we highlight some practical implications that can aid cloud storage providers in service design and adjustment decisions. This study contributes to the literature by providing a better understanding of the benefit structure and trade-offs user make in the choice of storage services. As an alternative to commercial conjoint software packages, we further contribute a method that can be adopted by other scholars who seek to conduct conjoint analyses using free software

Attitudes and acceptance of South African urban consumers towards genetically modified white maize

The introduction of genetically modified (GM) food products to food markets around the world, has led to considerable controversy. In many cases consumer attitudes and perceptions of GM food products were revealed as fears, concern for, and avoidance of the new technology. The importance of GM foods in South Africa is increasing, even though the GM Food debate lags behind many other (often more developed) parts of the world. This paper investigates the knowledge, attitudes and acceptance of urban South African white-grain maize consumers regarding GM maize. Conjoint- and cluster analysis were used to develop clusters/market segments among the urban consumers of white maize. A range of additional questions was used to develop profiles of the identified market segments. These aspects covered demographics, GM knowledge aspects as well as GM attitude aspects. Four distinct clusters/market segments were identified with specific characteristics: "Anti-GM, Brand aware" cluster (35% of valid responses), "Brand unaware, Farmer sympathetic" cluster (20%), "GM consumer benefit, Brand aware" cluster (25%) and the "Brand aware, Pro-GM" cluster (20%). The most significant differences between the clusters were based on the consumers' attitudes towards GM food products.Consumer/Household Economics,

The Value of Online Information Privacy: An Empirical Investigation

Concern over online information privacy is widespread and rising. However, prior research is silent about the value of information privacy in the presence of potential benefits from sharing personally identifiable information. Analyzing individuals' trade-offs between the benefits and costs of providing personal information to websites revealed that benefits, monetary reward and future convenience, significantly affect individuals' preferences over websites with differing privacy policies. Quantifying the value of website privacy protection revealed that among U.S. subjects, protection against errors, improper access, and secondary use of personal information is worth US $30.49 - 44.62. Finally, three distinct segments of Internet consumers were determined: privacy guardians, information sellers and convenience seekers.