A multidimensional data analysis of
questionnaire survey data on the sharing economy perceptions in Hong Kong using
the Excel pivot table function
JOSEPH KIM-KEUNG HO
Independent Trainer
Hong Kong, China
Dated: May 16, 2018
Abstract The Excel pivot table function (EPT) used for multidimensional data
analysis (MDA) should be considered as a research decision support system (DSS)
so that its value as a research tool can be better realized. This paper
provides some theoretical clarification on this proposition from the writer.
Specifically, it provides an
illustration on how the multidimensional data analysis is done with a EPT application on a data file on a 2015
questionnaire survey conducted by the writer with regard to the topic of
perceptions on the sharing economy in Hong Kong.
Key words: Excel
pivot table (EPT), The sharing economy perceptions survey data,
Multidimensional Data Analysis (MDA), Research Decision Support Systems (DSS).
Introduction
The Excel
pivot table function is a handy data analysis tool for multidimensional data
analysis. Ho (2018) further postulates that it could be conceived as a research
decision support system. In this paper, the writer employs the Excel pivot
table function to study a survey data set on the Hong Kong sharing economy
perceptions gathered by the writer in 2015 (Ho, 2015). The objectives are to:
(i) demonstrate the research decision support system practice with the Excel
pivot table and (ii) produce additional findings on Hong Kong sharing economy
perceptions based on the survey data set of Ho (2015). As such, the paper
should be of interested to those who study the subjects of research methods and
the sharing economy.
Using Excel pivot table function for
multidimensional data analysis
The Excel
pivot table function utilizes a flat data file in Excel, with the first row
consisting of field names and the subsequent rows as records. From the point of
view of the pivot table function, each field name indicates 1 dimension of the
topic to be examined. Thus, with a number of fields, the Excel pivot table
function promotes a multidimensional view of the topic under review. In
essence, the Excel pivot table function enables a convenient way to conduct
multidimensional data analysis on the researched topic. More than that, due to
its interactive interface that allows its user to produce multiple
2-dimensional-table views on the underlying data file, this pivot table
function enables its user to explore and exploit the data file to generate and
verify information in the analysis process. Therefore, the Excel pivot table
function has been recommended by Ho (2018) to be conceived as a research
decision support system, and not merely as a tool for the construction of
tables as descriptive statistics, which are often included in the chapter on
"findings and analysis" in a typical academic dissertation report.
The Excel pivot table is a decision support system as it consists of (i) a
database (i.e., the flat data file), (ii) a model base (i.e., a pivot table
template with a set of dimensions on the researched topic) and (iii) an
interactive and usable interface (i.e., the Excel pivot table construction
interface which allows for the creation of multiple 2-dimension table views on
the underlying data file). Because of that, Ho (2018) encourages researchers to
adopt decision support systems methodologies and practices to work with the Excel
pivot table function. The following example on the application of the Excel
pivot table function to a survey study of the Hong Kong sharing economy further
illustrates this research decision support system notion. This account
comprises two parts: the first part is a brief and updated introduction on the
sharing economy topic and the second part describes the actual Excel pivot
table function application on the survey data on the sharing economy
perceptions as reported in Ho (2015).
The main ideas underlying the topic of the
sharing economy in brief
Albeit
the "widespread ambiguity" of the term "sharing economy"
(Frenken and Schor, 2017), it is informative to conceive it in certain ways,
as, e.g., "consumers granting each other temporary access to under-utilized
physical assets ("idle capacity"), possibly for money" (Frenken
and Schor, 2017) and "a new culture of sharing.... in which people make
their belongings accessible through online networks" (Bucher, Fieseler and
Lutz, 2016; Zhang, Gu and Jahromi, 2018). The prime characteristics of the
contemporary sharing economy are (i) "stranger sharing" and (ii) the
sharing of "shareable goods"[1]
(Frenken and Schor, 2017) while the concept of "sharing sentient
beings" being more controversial (Yau, 2018). Böckman (2013) further examined the "sharing
economy" phenomenon in terms of the societal, economic and technological
drivers of it. Beyond that, Ho (2015) identifies six related study areas on the
"sharing economy" topic, namely, (i) the nature of sharing, (ii)
subcategories of the sharing economy, (iii) Information technology (IT)
platforms and infrastructures, (iv) business models and strategies, (v) impacts
and stakeholders' concerns, and (vi) recommended government policies and
regulations. This updated account of the sharing economy topic, which is
necessary brief, primarily serves to facilitate comprehension of the
multidimensional data analysis findings to be presented in the latter part of
this paper.
An application of Excel pivot table
function to study survey data on sharing economy perceptions in Hong Kong
The survey data to be studied with the Excel
pivot table function comes from the 2015 Facebook-based questionnaire survey
conducted by Ho (2015) on perceptions of the sharing economy in Hong Kong. By
using the Excel pivot table function to study this set of survey data, the
writer gives a demonstration of how the Excel pivot table function can be
employed as a research decision support system (Ho, 2018) as well as offers
additional analysis findings on the 2015 survey of the writer's sharing economy
perceptions study. The 2015 questionnaire survey, conducted in August 27 to 30,
consists of 18 questions , see appendix
1. The initial questions learn about the profiles of the survey respondents
while the subsequent questions record the respondents' perceptions on topics
related to the sharing economy practices and prospects in Hong Kong in 2015. By
cleansing the survey data, the writer is able to conduct a multidimensional
data analysis with the Excel as the research decision support system on them.
.... for further information, please download the pdf version.
[1] Shareable goods are "goods that by nature provide
owners with excess capacity, providing the consumer with an opportunity to lend
out or rent out their goods to other consumers" (Frenken and Schor, 2017).
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