Which Is the Best Parametric Statistical Method For Analyzing Delphi Data?

Shah, Hiral A.; Kalaian, Sema A.

doi:10.22237/jmasm/1241137140

Cited by 40 publications

(20 citation statements)

References 4 publications

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“…Table 6 summarizes the absolute difference between results of Delphi Round 1 and Round 2. Whilst [66] marked that values of [CV R1 -CV R2] below 0.2 are considered as minor, [65] added that henceforth the stopping rule is applied for the Delphi study. Noting such highlights, it is deduced that stability of each Severe DIF was reached at Round 2 and no further Delphi rounds were required.…”

Section: Results Stage 3 -Delphi Roundmentioning

confidence: 99%

“…Further computation to compare results from Delphi Round 2 and previous results from Delphi Round 1 was performed by exploiting a coefficient of variation [CV]. Parametric statistical methods such as the CV and F-test have been used in Delphi studies with samples below 50 as stated in [65] . The CV which defines ratio of standard deviation [SD] of a competency area to its corresponding means [AVG] among the Expert members was formulated as: [1] Accordingly, an absolute difference was calculated by subtracting the CV of the current and previous stage.…”

Section: Stage 2 -Delphi Roundmentioning

confidence: 99%

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Measuring Severity of Downtime Influence Factors to Naval Ship Operational Availability: A Delphi Study

Wahid¹,

Ahmad²,

Sunarsih³

et al. 2018

IJET

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Rapid development of shipbuilding and ship repair industry in recent years has been increasingly transforming the way organizations apply the long term strategic thinking of "cradle to grave" maintenance approach in order to maximize their growth in a dynamic marine industry. With increased ship complexity, size and revolutionary design, organizations strive to balance ideal maintenance philosophies against on-going efforts of cost reduction whilst maintaining high availability of vessels. Despite aspiration and efforts to improve the ship availability, the Royal Malaysian Navy [RMN] vessels which are currently maintained under the In Service Support [ISS] Contracts are hardly tackling the human and equipment related aspects due to limited knowledge and available data on ship Downtime Influence Factors [DIFs]. The current research carried out an explorative study across various engineering disciplines to generate RMN ship maintenance DIFs and their severity measures via a 3-Stage Modified Delphi approach. 30 Experts experienced in daily implementation of naval ship maintenance contracts were involved. In the first stage, Focus Group Discussions [FGDs] amongst Experts were conducted to produce the DIFs, followed by questionnaire distribution to measure the severity of the DIFs in the second stage. In the third stage, the Severe DIFs were confirmed and ranked based on a Risk Assessment method. The study revealed 50 DIFs to RMN ship availability and deduced the top 15 Severe DIFs pinpointing the key problem areas to prioritize efforts in improving RMN ship availability.

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Section: Results Stage 3 -Delphi Roundmentioning

confidence: 99%

Section: Stage 2 -Delphi Roundmentioning

confidence: 99%

Measuring Severity of Downtime Influence Factors to Naval Ship Operational Availability: A Delphi Study

Wahid¹,

Ahmad²,

Sunarsih³

et al. 2018

IJET

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“…Although there is no universal referent, consensus can be understood as "the degree of convergence of individual estimates to a minimum of 80 per cent" (Pozo, Gutiérrez & Rodríguez, 2007). The coefficient of variation provided by the experts' answers (S (x)=0.18) also indicates a high degree of consensus concerning the issues raised in the tool, since for (Shah & Kalaian, 2009) this coefficient is the most adequate test for this type of studies. Once the questionnaire structure was established, after the second consultation with the experts, the final design of the instrument was elaborated in telematic version, being its link: http://bit.ly/1EGNx4Y.…”

Section: Discussionmentioning

confidence: 98%

“…There is no a single way of estimating consensus (Arregui Ayatuy, Vallejo Alonso, & Villarreal Larrianaga, 1996, E. Martínez, 2003, Shah & Kalaian, 2009, Von der Gracht, Heiko A., 2012. Across the different possibilities, they can be the median or coefficient of variation because they are the most used in practice.…”

Section: Discussionmentioning

confidence: 99%

Design and Validation of the Questionnaire on the Initial Training Degree of Sports Coaches: QUGRAFOR®

Guillermo¹,

Esteban²,

Carlos³

2017

IJEE

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Abstract:The main objective of this research is to carry out a preliminary survey on the training of rugby coaches. To this end, an analysis was performed using the Delphi technique from a sample of 15 experts with extensive experience in training and teaching of this sport modality. It was implemented by elaborating a questionnaire of eight dimensions which must be taken into account in the preparation of rugby trainers: demographic variable, teaching experience, initial training, conception of rugby teaching, teaching methodology, personal aspects and training needs. This questionnaire was sent to some experts: the results show that most agree with all dimensions raised and 100% of them feel the need to know their teaching experience, the reasons for practising their profession, their training needs and their willingness to update their knowledge. Only some issuesconcerning their experience indifferent sports, and some repetitive aspects about the coachwork have been removed.

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“…Delphi surveys are typically analyzed with descriptive statistics (Hasson et al, 2000). However, inferential statistics in survey analysis provides more insights into the relationships between responses and rounds in surveys, including Delphi surveys (Hasson et al, 2000;Shah and Kalaian, 2009). Therefore, inferential statistics was used to analyze the data of this survey.…”

Section: Methodsmentioning

confidence: 99%

Modified Delphi Survey on Key Attributes for Selection of Water-treatment Technologies for Horticulture Irrigation

Raudales

Irani

Hall

et al. 2014

hortte

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A wide range of water-treatment technologies is used to control waterborne microbial problems in greenhouse and nursery irrigation. An online modified Delphi survey was carried out to identify the perceived key attributes that growers should consider when selecting among water-treatment technologies and to characterize a list of 14 technologies based on those same attributes. The expert panel consisted of ornamental plant growers (n = 43), water-treatment industry suppliers (n = 28), and research and extension faculty (n = 34). The survey was delivered to the expert panel in two rounds. Response rate was 59% and 60% for the first and second rounds, respectively. Growers identified control of plant disease, algae, and biofilm as primary reasons for adopting technologies, whereas mandatory regulation was not a major reason for adoption. All 23 attributes (related to cost, system size, control of microorganisms, chemistry, ease of use, and regulation) were perceived to be important when selecting between water-treatment technologies. Injectable sanitizing chemicals such as chlorination were considered to have low capital cost, unlike technologies that required installation of more complex equipment, such as heat treatment, hydrogen peroxide, ozone, reverse osmosis, or ultraviolet radiation. Filtration (excluding membrane filtration) was the only technology not perceived to be effective to control microorganisms. Filtration and copper were not considered effective to control human food-safety pathogens. Ozone was rated the highest as a technology that removes or oxidizes agrochemicals. Chemical water treatments, as opposed to physical water treatments, were perceived to be sensitive to water quality parameters and to have residual effect through the irrigation. Chlorine gas was perceived to be the only technology for which regulatory permission would be an obstacle. All technologies were perceived to be effective in water with low electrical conductivity (EC) or in solutions containing water-soluble fertilizers. This survey documents perceived attributes of water-treatment technologies, which are most useful where experimental data are not yet available. Research and outreach needs were highlighted by cases where perceived attributes differed from available experimental data or where there was a lack of consensus between experts.

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Which Is the Best Parametric Statistical Method For Analyzing Delphi Data?

Cited by 40 publications

References 4 publications

Measuring Severity of Downtime Influence Factors to Naval Ship Operational Availability: A Delphi Study

Measuring Severity of Downtime Influence Factors to Naval Ship Operational Availability: A Delphi Study

Design and Validation of the Questionnaire on the Initial Training Degree of Sports Coaches: QUGRAFOR®

Modified Delphi Survey on Key Attributes for Selection of Water-treatment Technologies for Horticulture Irrigation

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