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Stakeholder Mapping of CSR in Switzerland

2014· article· en· W3121242308 on OpenAlexaff
Stéphanie Looser, Walter Wehrmeyer

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsSurrey Place Centre
Fundersnot available
KeywordsCorporate social responsibilityMultinational corporationStakeholderBusinessLegitimacyStakeholder analysisPublic relationsBusiness ethicsStakeholder managementStakeholder engagementCentralityMarketingPolitical sciencePoliticsFinance

Abstract

fetched live from OpenAlex

Purpose - – This paper aims to investigate, using stakeholder map methodology, showing power, urgency, legitimacy and concerns of different actors, the current state of corporate social responsibility (CSR) in Switzerland. Previous research on CSR in Europe has made few attempts to identify stakeholders and their contribution to this topic. Design/methodology/approach - – To derive this map, publicly available documents were explored, augmented by 27 interviews with key stakeholders (consumers, media, government, trade unions, non-profit organisations [NPOs], banks, certifiers and consultants) and management of different companies (multinational enterprises [MNEs], small- and medium-sized enterprises [SMEs] and large national companies). Using MAXQDA, the quantified codes given for power, legitimacy and urgency were triangulated between self-reporting, external assessments and statements from publicly available documents and subsequently transferred into stakeholder priorities or, in other words, into positions in the map. Further, the codes given in the interviews for different CSR interests and the results from the document analysis were linked between stakeholders. The identified concerns and priorities were quantitatively analysed in regard to centrality and salience using VennMaker. Findings - – The paper identified SMEs, MNEs and cooperating NPOs as being the most significant stakeholders, in that order. CSR is, therefore, not driven primarily by regulators, market pressure or customers. Further network parameters substantiated the importance of SMEs while following an unconventionally informal and idiosyncratic CSR approach. Hence, insights into these ethics-driven, unformalised business models that pursue broader responsibility based on trust, traditional values, regional anchors and the willingness to “give something back” were formed. Examples of this strong CSR habit include democratic decisions and abolished hierarchies, handshake instead of formal contracts and transparency in all respects (e.g. performance indicators, salaries and bonuses). Research limitations/implications - – In total, 27 interviews as primary data that supplements publicly available documents are clearly only indicative. Practical implications - – The research found an innovative, vibrant and practical CSR model that is emerging for reasons other than conventional CSR agendas that are supposed to evolve. In fact, the stakeholder map and the CSR practices may point at a very different role businesses have adopted in Switzerland. Such models offer a useful, heuristic evaluation of the contribution of formal management systems (e.g. as could be found in MNEs) in comparison to the unformalised SME business conduct. Originality/value - – A rarely reported and astonishing feature of many of the very radical SME practices found in this study is that their link to commercial strategies was, in most cases, not seen. However, SMEs are neither the “poor relative” nor the abridged version of CSR, but are manifesting CSR as a Swiss set of values that fits the societal culture and the visionary goals of SME owners/managers and governs how a sustainably responsible company should behave. Hence, as a new stance and argument within CSR-related research, this paper concludes that “informal” does not mean “weak”. This paper covers a myriad of management fields, e.g. CSR as strategic tool in business ethics; stakeholder and network management; decision-making; and further theoretical frameworks, such as transaction cost and social capital theory. In other words, this research closes scientific gaps by at once applying quantitative as well as qualitative methods and by merging, for the first time, network methodology with CSR and stakeholder research.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0040.003
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.028
GPT teacher head0.233
Teacher spread0.206 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2014
Admission routes1
Has abstractyes

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