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Record W1937632984 · doi:10.1108/02634501311324889

Transferring knowledge for organisational customers by knowledge intensive business service marketing firms

2013· article· en· W1937632984 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMarketing Intelligence & Planning · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsCarleton University
Fundersnot available
KeywordsCustomer knowledgeKnowledge transferBusinessTacit knowledgeKnowledge managementKnowledge value chainCustomer advocacyBody of knowledgeMarketingService (business)Absorptive capacityCustomer retentionOrganizational learningService qualityComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine the knowledge transfer processes of knowledge intensive business service firms by focusing on the knowledge for customer, which is the knowledge about the service provider's products and services, specifically “before‐sale” knowledge, and the transfer of this knowledge in order to develop customers. Design/methodology/approach The authors conducted an in‐depth qualitative study of the knowledge transfer process undertaken by a sample of six global knowledge intensive service firms, to use knowledge transfer as a means of customer development. Findings The results of this study suggest that customer absorptive capacity influences the role that knowledge for customers has in ultimately determining whether customer development will occur. Where tacit knowledge transfer occurs, it is restricted to loyal, high share customers. With respect to methods of transfer, the findings reveal that knowledge‐intensive business service firms transferring explicit knowledge utilise both formal and informal methods. Research limitations/implications Data collection was cross‐sectional and longitudinal research would have the benefit of examining how customer knowledge transfer changes over time during the customer development process (pre‐sale, during sale and post‐sale customer development). Future research studying other types of knowledge transfer, such as during‐sale and after‐sale knowledge transfer, are also encouraged. Practical implications Managers should be open to employing numerous types of media in transferring both explicit and tacit knowledge rather than restricting themselves to the normative “explicit‐formal‐media lean” versus “tacit‐informal‐media rich” categorisations in the literature. Originality/value Understanding the role of customer knowledge transfer in the development of existing organisational customers is particularly important in the context of knowledge intensive business service firms. The extant literature recognises that customer development efforts are critically important in increasing service adoption and firm performance but there exists a dearth of research on customer knowledge transfer in the context of professional service organisations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.278
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it