Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 283

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Servitization and digitalization in manufacturing: the influence on firm performance

Open access
Martín-Peña, María-Luz, Sánchez-López, José-María, Díaz-Garrido, Eloísa·2019·Journal of Business & Industrial Marketing

Abstract

Purpose: This paper aims to present a comprehensive framework that integrates the emerging trends of servitization and digitalization in manufacturing. The influence between digitalization and servitization is defined and quantified. Their contribution to firm performance is analyzed. Design/methodology/approach: This paper presents a theoretical model that captures the relationships between the analyzed variables. Drawing on the Spanish Business Strategy Survey, hypothesis testing is conducted using data on 828 Spanish industrial firms. Linear regression models are built to capture the effect of each variable on firm performance and the type of interaction between the variables. Findings: Servitization and digitalization are positively related to firm performance. Digitalization positively mediates the relationship between servitization and firm performance. The mediating effect of digitalization contributes to differentiating between the direct and indirect effects of servitization on firm performance. Practical implications: The paper provides a useful analysis framework for firms to evaluate servitization and digitalization as success strategies. It is proposed that firms must simultaneously commit to digital transformation and the incorporation of services to create value, especially in business-to-business settings. Servitization and digitalization interact to exert a greater influence on performance. Originality/value: The paper contributes to the theory on service strategy by providing an analysis model that includes digitalization as a mediator of the relationship between servitization and firm performance. Digitalization may provide a mechanism to unlock the benefits of servitization and thereby enhance firm performance.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1108/jbim-12-2018-0400

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

Metadata

Authors
Martín-Peña, M.-L., Sánchez-López, J.-M., & Díaz-Garrido, E.
Venue
Journal of Business & Industrial Marketing
Publisher
Emerald
Published
2019-08-12
Volume
35
Issue
3
Pages
564-574
ISSN
0885-8624 (ISSN-L)
OpenAlex
W2971061501
Cited by
283
References
2
FWCI
30.61
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.