RAISE 4.0: A Readiness Assessment Instrument Aimed at Raising SMEs to Industry 4.0 Starting Levels – an Empirical Field Study

PurposeThe purpose of this paper is to present an Industry 4.0 Readiness Assessment Framework (I4.0RAF) and demonstrate its applicability and practical relevance through a case study of a large manufacturing firm in an emerging economy.Design/methodology/approachThe research firstly involved a synthesis of recent literature for the identification of important determinants, and their constituent criteria, for assessing the readiness of a manufacturing firm to transition to an Industry 4.0 setting and structuring them into a readiness assessment framework that can be used as a self-diagnostic tool. The framework was illustrated through a case study. The empirical findings of readiness assessment are validated using semi-structured interviews of senior management of the organization.FindingsThe proposed I4.0RAF was found to be a practically applicable self-diagnostic tool that can be used to assess a firm's readiness to transition to an Industry 4.0 setting with respect to eight important determinants. Cross-functional participation in the assessment helped the organization to determine priorities and interdependencies among the determinants.Research limitations/implicationsThe determinants and their constituent criteria can be further streamlined using inputs from practitioners, consultants and academics.Practical implicationsThe findings demonstrate the interdependencies between the determinants, help to delineate interventions that can lead to synergistic outcomes and enabls planning to achieve higher levels of Industry 4.0 maturity.Originality/valueA self-diagnostic tool as a basis for an informed discussion on transitioning to an Industry 4.0 setting is presented and illustrated through a case study in an emerging economy.

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Applying Simplifying Heuristics when Making Judgment under Uncertainty – A Field Study

Journal of Economics and Business ◽

10.31014/aior.1992.03.04.290 ◽

2020 ◽

Vol 3 (4) ◽

Author(s):

Tristan Nguyen ◽

Keyword(s):

Field Study ◽

Choice Task ◽

Decision Makers ◽

The Other ◽

Final Choice ◽

Take The Best ◽

Empirical Field

This paper studies the so-called Take the Best (TTB) and the other two related heuristics which are Take the last (TTL) and the Minimalist heuristics to collect more evidence on these heuristics and then make comparison on performance of these heuristics’ potential users who have different degree of knowledge. People actually adhere to the recognition heuristics (RH) so often when facing inferential choice between a recognized object and a novel one. It is a main purpose of our empirical field study to look for evidence on what decision makers really do to arrive at their final choice in cases where both objects in the choice task are recognized. Will they still stick to recognition cue, or will they follow TTB or TTL or the Minimalist heuristic or will they resort to other type of strategies? Our results are somehow ambiguous. In sum, the cues the participants really picked up from their minds when taking the task and revealed by themselves in the interviews are more diverse and complicated than the anticipated ones.

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A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises

Sustainability ◽

10.3390/su12093559 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3559 ◽

Cited By ~ 6

Author(s):

Erwin Rauch ◽

Marco Unterhofer ◽

Rafael A. Rojas ◽

Luca Gualtieri ◽

Manuel Woschank ◽

...

Keyword(s):

Field Study ◽

Industry 4.0 ◽

Assessment Tool ◽

Assessment Model ◽

Manufacturing Companies ◽

Research To Practice ◽

Maturity Level ◽

The Past ◽

Industrial Companies ◽

Individual Strategy

Industry 4.0 has attracted the attention of manufacturing companies over the past ten years. Despite efforts in research and knowledge transfer from research to practice, the introduction of Industry 4.0 concepts and technologies is still a major challenge for many companies, especially small and medium-sized enterprises (SMEs). Many of these SMEs have no overview of existing Industry 4.0 concepts and technologies, how they are implemented in their own companies, and which concepts and technologies should primarily be focused on future Industry 4.0 implementation measures. The aim of this research was to develop an assessment model for SMEs that is easy to apply, provides a clear overview of existing Industry 4.0 concepts, and supports SMEs in defining their individual strategy to introduce Industry 4.0 in their firm. The maturity level-based assessment tool presented in this work includes a catalog of 42 Industry 4.0 concepts and a norm strategy based on the results of the assessment to support SMEs in introducing the most promising concepts. For testing and validation purposes, the assessment model has been applied in a field study with 17 industrial companies.

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Readiness assessment for the use of cloud computing in eHealth systems: A field study of hospitals in the capital of Azerbaijan

2016 HONET-ICT ◽

10.1109/honet.2016.7753437 ◽

2016 ◽

Author(s):

Saleh Ahmadzada ◽

Musa A. Zayyad ◽

Mehmet Toycan

Keyword(s):

Cloud Computing ◽

Field Study ◽

Readiness Assessment

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To forget or to remember: Denial deflation effect and subjective confidence of autobiographical memories

Psychology and Law ◽

10.17759/psylaw.2015100210 ◽

2015 ◽

Vol 10 (2) ◽

pp. 126-137 ◽

Cited By ~ 2

Author(s):

V.V. Нуркова

Keyword(s):

Field Study ◽

Forensic Psychology ◽

Memory Performance ◽

Specific Effect ◽

Legal Issues ◽

Autobiographical Memories ◽

Lasting Effect ◽

Subjective Confidence ◽

Empirical Field

The paper focuses on the problem of the long-lasting effect of deliberate lie on autobiographical memories, which seems to be of extreme importance for forensic psychology. Firstly, the literature on autobiographical memory’s malleability is reviewed in the context of legal issues. Then we present the empirical field study carried out to examine dynamics of confidence toward episodes of personal past after participants had been instructed a) to retell a false episode as true; b) to retell a false episode as false; c) to deny the reality of a true episode. We coined the main finding as “Denial deflation”. This effect exists in two forms. The first is forgetting of falsely denied true episode. The second is mistaken acceptance of truthfully denied false episode. Our findings indicate that the act of lying produces specific effect on memory performance both for intentional creation of false story and for intentional denial of true experience.

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Industry 4.0 Readiness Assessment

Tehnički glasnik ◽

10.31803/tg-20200523195016 ◽

2020 ◽

Vol 14 (2) ◽

pp. 212-217 ◽

Cited By ~ 1

Author(s):

Bernhard Axmann ◽

Harmoko Harmoko

Keyword(s):

Data Storage ◽

Industry 4.0 ◽

Assessment Tool ◽

Small And Medium Enterprises ◽

Quality Data ◽

Readiness Assessment ◽

The Road ◽

On The Road ◽

The Right ◽

Medium Enterprises

This research aims to establish an assessment tool for assessing the readiness of small and medium enterprises (SME) in industry 4.0. The assessment of the current and future status is crucial for companies to decide on the right strategy and actions on the road to a digital company. First will be compared existing tools such as: IMPULS (VDMA), PwC and Uni-Warwick. On that basis, a tool for SME will be introduce. The tool has 12 categories: data sharing, data storage, data quality, data processing, product design and development, smart material planning, smart production, smart maintenance, smart logistic, IT security, machines readiness and communication between machines. Those categories are grouped into three: data, software and hardware. Each category has five levels of readiness (from 1 to 5), with particular criteria that refer to literature studies and expert’s opinion.

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Indian supply chain ecosystem readiness assessment for Industry 4.0

International Journal of Emerging Markets ◽

10.1108/ijoem-08-2020-0983 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Shubham Tripathi ◽

Manish Gupta

Keyword(s):

Supply Chain ◽

Industry 4.0 ◽

Industrial Revolution ◽

Business Environment ◽

Government Support ◽

Readiness Assessment ◽

Content Type ◽

Start Up ◽

Transformation Potential ◽

Two Stages

PurposeThe article analyses the current readiness of India to transform its supply chain ecosystem to smarter systems with Fourth Industrial Revolution.Design/methodology/approachThe analysis is carried out in two stages. First, the readiness of India is assessed globally, and then the rate of transformation over the years and supporting policies are analyzed to understand the transformation potential. This analysis is done across nine identified macro factors namely government support, regulations, business environment, human resource, infrastructure, innovation capability, technological advancements, cybersecurity and digital awareness. The study combines empirical data from 2010 onwards with the strategic literature published by government bodies and institutions for analysis.FindingsResults show that India's readiness is just above the global average with a score of 0.44 on a scale of 0–1 (most ready). Government and start-up culture are found to be leading transformation factors, while digital infrastructure, regulations and cybersecurity are most lacking areas.Originality/valueThis study is first of its kind to the best of our knowledge. The academic literature has not reported studies assessing Industry 4.0 readiness of supply chain ecosystem using macro factors for nations.

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