No abstract

Collaboration is becoming a new current paradigm for product manufacturing, as computer networks facilitate collaboration with partners located in widely distributed locations. Computer network technologies allow a large number of candidate partners to be examined for possible collaboration, so that the most suitable partner, or partners, can be selected from a broader, more diverse group than previously possible. In order to take best advantage of the collaboration paradigm, the precise method for selecting collaborative product development partners is an important technological point. Failed multicompany collaboration projects can do serious harm to the member companies on a number of fronts, in terms of financial cost, loss of prestige, loss of market share, and so on. The optimal collaboration partners should be selected from a group of candidates, so that production of new products can be achieved at a minimum cost, both financial and in terms of effort and expended resources. This paper proposes a decision supporting method for selecting an optimum collaborative product development partner from a group of potential partners. First, the effectiveness of collaborative product development and the need for a partner selection method is clarified. Next, a method for selecting the most suitable product development partner is constructed. Here, technologies that are required for developing the new product are classified into two groups: (1) technologies that have already been developed, and (2) technologies that must be newly developed. The proposed method first excludes unsuitable candidate partners, based on their achievement level concerning existing required technologies, and then selects the most suitable partner from the standpoint of technologies that must be newly developed. Finally, a case study is given to demonstrate the utility of the proposed method.

The type of processing-resource allocation (TOPRA) model predicts that the semantic processing of new second language (L2) words can impede the learning of their forms while structural processing can promote it. Using this framework, the present study examined the effects of processing type (semantic, structural, control), exposure frequency (one exposure, three exposures), and their combination on the learning of new L2 words through reading. Adult Japanese learners of English read a reading text that contained 10 target words, five of them were repeated only one time whereas the other five were repeated three times. They were asked to answer some comprehension questions as their primary task, and the participants in the semantic and structural processing groups were asked to perform the secondary vocabulary processing tasks (pleasantness rating and phonological recording, respectively) to further process target word meanings or forms. The unexpected first language (L1)-to-L2 and L2-to-L1 cued recall were administered. The positive effects of structural processing and exposure frequency were demonstrated in L1-to-L2 cued recall. The results further suggested that effects of vocabulary processing type and exposure frequency vary depending on how vocabulary gain is measured.

The type of processing–resource allocation (TOPRA) model predicts that increasing one type of processing (semantic, structural, or mapping oriented) can decrease other types of processing and their learning counterparts. This study examined how semantic and structural tasks affect the mapping component of second language (L2) vocabulary learning. Japanese-speaking L2 English learners attempted to map secondary meanings of 24 English homographs. Each participant studied them (a) while making pleasantness ratings about word meaning (mapping plus semantic processing); (b) while counting letters in each word (mapping plus structural processing); and (c) without any additional task (mapping only). Results of L1 (first language) and L2 free recalls and L2-to-L1 and L1-to-L2 cued recalls indicated higher free recall in the semantic condition over the structural condition and higher cued recall in the mapping condition over the semantic and structural conditions, providing qualitatively new evidence for TOPRA model predictions.

In a masked form priming lexical decision task, orthographically related word primes cause null or inhibitory priming relative to unrelated controls because of lexical competition between primes and targets, whereas orthographically related nonword primes lead to facilitation because nonwords are not lexically represented and hence do not evoke lexical competition. This prime lexicality effect (PLE) has been used as an index of new word lexicalization in the developing lexicon by using to-be-learned words and their orthographic neighbors as primes and targets, respectively. Experiment 1 confirmed an inhibitory effect of −46 ms among native English speakers and faciliatory effects of 52 ms by Japanese English learners without critical word training. In Experiment 2, Japanese English learners studied novel English words while performing a meaning-based, form-based, or no task during learning. Recall measures indicated a dissociation between these two types of processing, with a form-based task leading to greater recall of L2 words and a meaning-based task leading to greater recall of L1 words. Results indicated that all three learning conditions produced neither facilitation nor inhibition (null priming effect). Taken together, the results of the two experiments demonstrate that the PLE can occur in a second language (L2) and that the training procedure can yield at least partial lexicalization of new L2 words.