The prescriptive quality of 11 design principles for knowledge productivity

This study explores the learning processes that contribute to knowledge productivity: gradual improvement and radical innovation of an organisation’s operating procedures, products, and services, based on the development and application of new knowledge. The research is based on the assumption that innovation is the result of a series of powerful social learning processes. Previous research revealed a set of eleven design principles that reflect factors that really matter in an innovation process. The study at hand presents how these design principles facilitate the design of an innovation practice. Review workshops and design workshops were used to answer the main research question: How do the design principles facilitate the design of an innovation practice? The data reveals that the design principles do not work as prescriptive rules that in a specific combination, applied to a predefined situation, will result in certain effects. Every design principle offers a new perspective on the innovation practice. This new perspective helps to get new ideas for interventions in the innovation practice. After the design of these interventions it is mainly the facilitator who has an important role in making it a success. If he sees opportunities and is capable, then he can use the interventions to create breakthroughs in the innovation practice

Optimal designs for conjoint experiments.

Design; Model-sensitive; Optimal; Optimal design; Data;

Optimal two-level conjoint designs for large numbers of attributes.

In this paper, we propose a simple strategy to construct D-, A-, G- and V-optimal two-level multi-attribute designs for rating-based conjoint studies. Our approach combines orthogonal designs and balanced or partially balanced incomplete block designs. In order not to overload respondents with complicated tasks, the designs hold one or more attributes at a constant level. The designs are variance-balanced meaning that they yield an equal amount of information on each of the part-worths. Some examples are provided to illustrate the method.Balanced and partially balanced incomplete block designs; D-,A-,G- and V-optimality; Orthogonal designs; Two-level conjoint designs; Strategy; Design; Studies; Order; Yield; Information;

A single-system model predicts recognition memory and repetition priming in amnesia

We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit

Comparing algorithms and criteria for designing Bayesian conjoint choice experiments.

The recent algorithm to find efficient conjoint choice designs, the RSC-algorithm developed by Sándor and Wedel (2001), uses Bayesian design methods that integrate the D-optimality criterion over a prior distribution of likely parameter values. Characteristic for this algorithm is that the designs satisfy the minimal level overlap property provided the starting design complies with it. Another, more embedded, algorithm in the literature, developed by Zwerina et al. (1996), involves an adaptation of the modified Fedorov exchange algorithm to the multinomial logit choice model. However, it does not take into account the uncertainty about the assumed parameter values. In this paper, we adjust the modified Fedorov choice algorithm in a Bayesian fashion and compare its designs to those produced by the RSC-algorithm. Additionally, we introduce a measure to investigate the utility balances of the designs. Besides the widely used D-optimality criterion, we also implement the A-, G- and V-optimality criteria and look for the criterion that is most suitable for prediction purposes and that offers the best quality in terms of computational effectiveness. The comparison study reveals that the Bayesian modified Fedorov choice algorithm provides more efficient designs than the RSC-algorithm and that the Dand V-optimality criteria are the best criteria for prediction, but the computation time with the V-optimality criterion is longer.A-Optimality; Algorithms; Bayesian design; Bayesian modified Fedorov choice algorithm; Choice; Conjoint choice experiments; Criteria; D-Optimality; Design; Discrete choice experiments; Distribution; Effectiveness; Fashion; G-optimality; Logit; Methods; Model; Multinomial logit; Predictive validity; Quality; Research; RSC-algorithm; Studies; Time; Uncertainty; V-optimality; Value;

Optimal designs for rating-based conjoint experiments.

The scope of conjoint experiments on which we focus embraces those experiments in which each of the respondents receives a different set of profiles to rate. Carefully designing these experiments involves determining how many and which profiles each respondent has to rate and how many respondents are needed. To that end, the set of profiles offered to a respondent is viewed as a separate block in the design and a respondent effect is incorporated in the model, representing the fact that profile ratings from the same respondent are correlated. Optimal conjoint designs are then obtained by means of an adapted version of the algorithm of Goos and Vandebroek (2004). For various instances, we compute the optimal conjoint designs and provide some practical recommendations.Conjoint analysis; D-Optimality; Design; Model; Optimal; Optimal block design; Rating-based conjoint experiments; Recommendations;

Knowledge work in successful supermarkets: Shop assistants as innovators

Managers constantly seek for innovative ideas to improve their organisations. Their staff, sometimes supported by external consultants should then develop these ideas further and implement the results in the organisation. This does not always work out the way intended. In this paper we examined this process of change in the case of a supermarket chain in the Netherlands. The aim was to learn from successful supermarkets how the employees in these shops contribute to the change of their work environment. We also looked for interventions that stimulate the knowledge worker’s contribution to this process. Our research in 17 supermarkets revealed that it is necessary to allow for diversity; that ownership and entrepreneurship contribute more to change than discipline and obedience; and that the specific role and capability of the manager seems to be crucial. Staff needs to develop competencies that match their own ability and interests in order to successfully innovate in the supermarket. In order to become innovative shop employees should be granted the authority to engage in knowledge work. In the supermarkets that we visited during the research, we found various interventions that could support the development of ownership and entrepreneurship of the supermarket staff

De vele verschijningen van leiderschap. Leiderschapsontwikkeling (18): epiloog

Bestaat er zoiets als nieuw leiderschap en wat is dan het oude leiderschap? Hoe beoordelen verschillende organisaties het belang van leiderschapsontwikkeling, door welke visies laten zij zich inspireren en welke modellen en trajecten gebruiken zij daarbij

Andragogy

The main focus of andragogy has been: helping adults learn and develop, creating favorable conditions for learning and development in a work environment as well as in their private lives. The development of andragogy has close relationships with adult education and HRD and encountered major debates on its assumptions and scientific foundations. The critical approach of andragogy still offers a meaningful contribution to HRD in an emerging knowledge society